Triple
T9480582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chingford |
E228624
|
entity |
| Predicate | hasBusServicesTo |
P3791
|
FINISHED |
| Object | Woodford |
E283345
|
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: Woodford | Statement: [Chingford, hasBusServicesTo, Woodford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Woodford Context triple: [Chingford, hasBusServicesTo, Woodford]
-
A.
Woodford
chosen
Woodford is a suburban area in East London, England, known for its residential character and connectivity on the London Underground network.
-
B.
Woodford
Woodford is a town in Greater Manchester, England, historically notable for its large Avro aircraft manufacturing plant.
-
C.
Marwood
Marwood is the anxious, aspiring actor and narrator who accompanies the flamboyant Withnail in the British cult film "Withnail & I."
-
D.
Fleetwood
Fleetwood is a residential neighborhood in the city of Mount Vernon, New York, known for its suburban character and proximity to New York City.
-
E.
Fleetwood
Fleetwood is a coastal town and historic port in Lancashire, England, known for its maritime heritage and role as a ferry and fishing hub.
- 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_69ca84730a5081908de282651019bf2f |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd8018645c8190823d82a93635b345 |
completed | April 1, 2026, 8:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d12cfebb6c8190af3296c7bfd8b3e4 |
completed | April 4, 2026, 3:23 p.m. |
Created at: March 30, 2026, 7:54 p.m.