Triple
T682291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brentford |
E13207
|
entity |
| Predicate | hasMarketTownHistory |
P17485
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [Brentford, hasMarketTownHistory, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMarketTownHistory Context triple: [Brentford, hasMarketTownHistory, true]
-
A.
hasHistoricCity
Indicates that an entity possesses, contains, or is associated with a city recognized for its historical significance.
-
B.
hasHistoricCountySeat
Indicates that an administrative region historically had its county government or main county offices located in a particular settlement or city.
-
C.
hasTown
Indicates that one entity possesses, contains, or is associated with a town as part of its structure, jurisdiction, or composition.
-
D.
hasHistoricDistrict
Indicates that an entity possesses or contains a designated historic district within its boundaries or domain.
-
E.
hasNotableTown
Indicates that an entity includes or is associated with a town that is considered notable or significant in some way.
- F. None of above. chosen
Provenance (4 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a06f9ee88190a2d757aacd8e3f5b |
completed | March 1, 2026, 8:24 p.m. |
| PD | Predicate disambiguation | batch_69a49d1f0ccc819088c1527beabcb718 |
completed | March 1, 2026, 8:10 p.m. |
| PDg | Predicate description generation | batch_69a49df19c9481909cc9bc33ed7f011b |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:36 p.m.