Triple

T10997375
Position Surface form Disambiguated ID Type / Status
Subject William Hartnett E259912 entity
Predicate hasShortForm P43 FINISHED
Object Will Hartnett
Will Hartnett is an American attorney and Republican politician who served as a member of the Texas House of Representatives.
E901951 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: Will Hartnett | Statement: [William Hartnett, hasShortForm, Will Hartnett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Will Hartnett
Context triple: [William Hartnett, hasShortForm, Will Hartnett]
  • A. Steve Hartnett
    Steve Hartnett is an individual notable enough to be specifically cited as a bearer of the surname Hartnett.
  • B. Frank Hartnett
    Frank Hartnett is a notable individual distinguished enough in his field or public life to be recognized as a prominent bearer of the Hartnett surname.
  • C. Tom Hartnett
    Tom Hartnett is a notable individual distinguished enough to be recognized as a prominent bearer of the Hartnett surname.
  • D. Sean Hartnett
    Sean Hartnett is a relatively obscure individual whose primary distinguishing feature is sharing the surname Hartnett, with no widely recognized public profile or achievements documented.
  • E. Ed Hartnett
    Ed Hartnett is an American software developer best known as the creator and primary maintainer of the NetCDF-4 library widely used in scientific computing and data analysis.
  • 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: Will Hartnett
Triple: [William Hartnett, hasShortForm, Will Hartnett]
Generated description
Will Hartnett is an American attorney and Republican politician who served as a member of the Texas House of Representatives.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Will Hartnett
Target entity description: Will Hartnett is an American attorney and Republican politician who served as a member of the Texas House of Representatives.
  • A. Steve Hartnett
    Steve Hartnett is an individual notable enough to be specifically cited as a bearer of the surname Hartnett.
  • B. Frank Hartnett
    Frank Hartnett is a notable individual distinguished enough in his field or public life to be recognized as a prominent bearer of the Hartnett surname.
  • C. Tom Hartnett
    Tom Hartnett is a notable individual distinguished enough to be recognized as a prominent bearer of the Hartnett surname.
  • D. Sean Hartnett
    Sean Hartnett is a relatively obscure individual whose primary distinguishing feature is sharing the surname Hartnett, with no widely recognized public profile or achievements documented.
  • E. Ed Hartnett
    Ed Hartnett is an American software developer best known as the creator and primary maintainer of the NetCDF-4 library widely used in scientific computing and data analysis.
  • 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_69d6aa8a6a548190a750f944ccdc8064 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d796d20b448190958331705de3a9be completed April 9, 2026, 12:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3a9644ff08190a3005e4f6a8243fe completed April 18, 2026, 3:55 p.m.
NEDg Description generation batch_69e3ad00b5c08190a7bf3ecbeae76d88 completed April 18, 2026, 4:10 p.m.
NED2 Entity disambiguation (via description) batch_69e3b1efe4a88190884eb5186954cf39 completed April 18, 2026, 4:31 p.m.
Created at: April 8, 2026, 9:24 p.m.