Triple
T2986207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hayes railway line |
E80630
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Hayes |
E48908
|
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: [Hayes railway line, serves, Hayes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hayes Context triple: [Hayes railway line, serves, Hayes]
-
A.
Hayes
chosen
Hayes is a suburban district in southeast London, England, known for its residential character and green spaces within the London Borough of Bromley.
-
B.
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.
-
C.
Harbison
Harbison is a surname most notably associated with American composer John Harbison, known for his contributions to contemporary classical music.
-
D.
Everette
Everette is the given first name of E. Howard Hunt, the American intelligence officer and author involved in the Watergate scandal.
-
E.
Wylie
Wylie is a suburban city in the Dallas–Fort Worth metropolitan area in northeastern Texas.
- 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_69ad8b16c3488190b47b6aa7a59a335b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99c76dfc8190b08bd6110ffabf25 |
completed | March 8, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b12e3654388190beeb1c6b2a629b85 |
completed | March 11, 2026, 8:56 a.m. |
Created at: March 8, 2026, 2:59 p.m.