Triple
T3851070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pitt the Elder |
E85294
|
entity |
| Predicate | deathPlace |
P21
|
FINISHED |
| Object | Hayes |
E325830
|
NE FINISHED |
How this triple was built (2 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: Hayes | Statement: [Pitt the Elder, deathPlace, Hayes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hayes Context triple: [Pitt the Elder, deathPlace, Hayes]
-
A.
Hayes
Hayes is a suburban district in southeast London, England, known for its residential character and green spaces within the London Borough of Bromley.
-
B.
Hayes
chosen
Hayes is a suburban town in west London, England, known for its residential areas, transport links, and proximity to Heathrow Airport.
-
C.
Hayden
Hayden is a surname most notably associated with American actor and author Sterling Hayden, known for his roles in classic mid-20th-century films.
-
D.
Grier
Grier is the surname of Pam Grier, an influential American actress renowned for her groundbreaking roles in 1970s blaxploitation films.
-
E.
Harbison
Harbison is a surname most notably associated with American composer John Harbison, known for his contributions to contemporary classical music.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeebcf67788190975105131baabc4b |
completed | March 9, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b50419e7a0819087f9bc7fbfec4116 |
completed | March 14, 2026, 6:45 a.m. |
Created at: March 9, 2026, 3:19 p.m.