Triple
T5898414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uxbridge |
E131158
|
entity |
| Predicate | hasNearbyPlace |
P3449
|
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: [Uxbridge, hasNearbyPlace, Hayes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hayes Context triple: [Uxbridge, hasNearbyPlace, 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
Hayes is a common English surname borne by numerous notable figures in politics, entertainment, sports, and other fields.
-
C.
Hayes
chosen
Hayes is a suburban town in west London, England, known for its residential areas, transport links, and proximity to Heathrow Airport.
-
D.
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.
-
E.
Hayden
Hayden is a small city in northern Idaho, known for its proximity to Hayden Lake and its role as part of the Coeur d'Alene metropolitan area.
- 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_69c00857439c819095950754176aa58a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c036f7b3f48190a499d43f8ffb2fa7 |
completed | March 22, 2026, 6:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b15df86481908b59717b9de63655 |
completed | March 23, 2026, 3:19 a.m. |
Created at: March 22, 2026, 3:58 p.m.