Output Explorer

Every prompt in the paper, and what each model wrote back.

Extract seven entity types from one sentence of financial news as JSON. Scored per field against the Cleanlab reference.

13 of 2,117 prompts

In January 2013 , Alliant Energy sold its remaining interest in RMT , Inc. ( RMT ) .Mr. Phillips co - founded Meta Systems in May 1991 .We have purchased assets from TransCanada and jointly participated with TransCanada in acquiring assets from third parties , including acqui Mr. Georgiadis resignation was voluntary ; it was the result of the prior agreement and understanding under which Mr. Rosenbaum acquired the Our Vogue - Show subsidiary rents 96 square meters of office space from Wuhan Kingold at an annual rental rate of $ 1,500 per year .Divestitures In March 2011 , LCNB Corp. sold Dakin Insurance Agency Inc. ( Dakin ) to an independent insurance agency and therefore its fina In fiscal 2012 , an outside director who had been serving on the Company s Board of Directors for the prior six months was granted upon re -In support of this business , we use a fleet of approximately 450 tractor - trailer tank trucks , the majority of which we lease and operate We also own approximately 120 local operating facilities with front office administration and sales office space connected to back - shop po ( 7 ) William J. Robison , a director of the Company , has direct ownership of 168,713 shares .On May 24 , 2012 , the Company entered into the 2013 Lease Agreement covering the ten TC hospitals that were otherwise scheduled to expire o In addition , the Bank operates 31 automated teller machines ( " ATMs " ) in its market area .( b ) Includes an outstanding option to purchase 350,000 shares of common stock granted to Robert P. Gasparini , our Chief Scientific Office

Nearby prompts. All 2,117 FIRE entities prompts

PromptCleanlab FIRE ·fire-0743

In fiscal 2012 , an outside director who had been serving on the Company s Board of Directors for the prior six months was granted upon re - election by the shareholders at the annual general meeting an option to purchase 9,000 common shares immediately following each annual general meeting of shareholders .

Extraction instructions · system prompt, 2,489 characters, identical for every model

Identify and extract entities from the following financial news text into the following categories:

Entity 1: Company 
⋆ Definition: Denotes the official or unofficial name of a registered company or a brand.
⋆ Example entities: {Apple Inc.; Uber; Bank of America}

Entity 2: Date 
⋆ Definition: Represents a specific time period, whether explicitly mentioned (e.g., "year ended March 2020") or implicitly referred to (e.g., "last month"), in the past, present, or future.
⋆ Example entities: {June 2nd, 2010; quarter ended 2021; last week; prior year; Wednesday}

Entity 3: Location 
⋆ Definition: Represents geographical locations, such as political regions, countries, states, cities, roads, or any other location, even when used as adjectives.
⋆ Example entities: {California; Paris; 1280 W 12th Blvd; Americas; Europe}

Entity 4: Money 
⋆ Definition: Denotes a monetary value expressed in any world currency, including digital currencies.
⋆ Example entities: {$76.3 million; $4 Bn; Rs 33.80 crore; 1.2 BTC}

Entity 5: Person 
⋆ Definition: Represents the name of an individual.
⋆ Example entities: {Meg Whitman; Mr. Baker; Warren Buffet}

Entity 6: Product 
⋆ Definition: Refers to any physical object or service manufactured or provided by a company to consumers, excluding references to businesses or sectors within the financial context.
⋆ Example entities: {iPhone; Tesla model X; cloud services; Microsoft Windows 10; laptops; medical equipment; computer software; online classes; eye surgery}

Entity 7: Quantity 
⋆ Definition: Represents any numeric value that is not categorized as Money, such as percentages, numbers, measurements (e.g., weight, length), or other similar quantities. Note that unit of measurements are also part of the entity.
⋆ Example entities: {15%; 25,000 units; 2.75in; 100 tons}

For each category:
- Extract all relevant entities as a list of strings, preserving the wording from the text
- Use None if no entities are found in that category
- Only extract entities that are explicitly mentioned in the text itself, do not make inferences or reason about what entities might be implied based on URLs, domain names, or other indirect references
- Extract individual items rather than compound or ranged entities (e.g., if a range or compound entity is mentioned, extract each individual item separately)

Return the extracted information as a JSON object with all categories included, using None for cases where no entities are found.

Expected answer

Company: none
Date: fiscal 2012
Location: none
Money: none
Person: none
Product: none
Quantity: 9,000

Ours

6 of 7 fields correct

```json
{
  "Company": None,
  "Date": [
    "fiscal 2012",
    "prior six months"
  ],
  "Location": None,
  "Money": None,
  "Person": None,
  "Product": None,
  "Quantity": [
    "9,000"
  ]
}
```

Aux 2015

Invalid JSON

{
  "Company": {

PiT-FT 2015

Invalid JSON

Empty response.

ChronoGPT 2015

Invalid JSON