Triple

T17593007
Position Surface form Disambiguated ID Type / Status
Subject Textron E428491 entity
Predicate tickerSymbol P1447 FINISHED
Object TXT
TXT is the stock ticker symbol for Textron Inc., a U.S.-based industrial conglomerate known for its aerospace, defense, and specialized vehicle businesses.
 E1276132 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: TXT | Statement: [Textron, tickerSymbol, TXT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TXT
Context triple: [Textron, tickerSymbol, TXT]
  • A. ARD Text
    ARD Text is the teletext service of the German public broadcaster ARD, providing news, information, and program details via television text pages.
  • B. TextEdit
    TextEdit is a simple, built-in macOS application for creating and editing plain text and rich text documents.
  • C. Texing
    Texing is a small municipality in Lower Austria, known primarily as the birthplace of Austrian chancellor Engelbert Dollfuss.
  • D. textutils
    textutils was the former name of a collection of GNU command-line text processing utilities that were later consolidated into the GNU Core Utilities package.
  • E. C-text
    C-text is one of the principal textual versions of the Middle English allegorical poem *Piers Plowman*, representing a distinct editorial and manuscript tradition within its complex transmission history.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: TXT
Triple: [Textron, tickerSymbol, TXT]
Generated description
TXT is the stock ticker symbol for Textron Inc., a U.S.-based industrial conglomerate known for its aerospace, defense, and specialized vehicle businesses.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TXT
Target entity description: TXT is the stock ticker symbol for Textron Inc., a U.S.-based industrial conglomerate known for its aerospace, defense, and specialized vehicle businesses.
  • A. ARD Text
    ARD Text is the teletext service of the German public broadcaster ARD, providing news, information, and program details via television text pages.
  • B. TextEdit
    TextEdit is a simple, built-in macOS application for creating and editing plain text and rich text documents.
  • C. Texing
    Texing is a small municipality in Lower Austria, known primarily as the birthplace of Austrian chancellor Engelbert Dollfuss.
  • D. textutils
    textutils was the former name of a collection of GNU command-line text processing utilities that were later consolidated into the GNU Core Utilities package.
  • E. C-text
    C-text is one of the principal textual versions of the Middle English allegorical poem *Piers Plowman*, representing a distinct editorial and manuscript tradition within its complex transmission history.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d889e1030481909950e140c63255b9 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e469e89acc81908e52138ad4f452c6 completed April 19, 2026, 5:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01ddf81ea0819080e9324e3e72cc47 completed May 11, 2026, 1:47 p.m.
NEDg Description generation batch_6a01dee081c081909a6a6cbce547aba8 completed May 11, 2026, 1:51 p.m.
NED2 Entity disambiguation (via description) batch_6a01df96182c81909bc3f399ccc589f9 completed May 11, 2026, 1:54 p.m.
Created at: April 10, 2026, 5:51 a.m.