Triple
T2346220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Lea |
E45136
|
entity |
| Predicate | flowsThroughSettlement |
P9749
|
FINISHED |
| Object | Enfield |
E123079
|
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: Enfield | Statement: [River Lea, flowsThroughSettlement, Enfield]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Enfield Context triple: [River Lea, flowsThroughSettlement, Enfield]
-
A.
Enfield
chosen
Enfield is a historic town in north London that developed from a Middlesex market settlement into a major suburban and commercial center.
-
B.
Enfield
Enfield is a small rural town located in Tompkins County in the Finger Lakes region of New York State.
-
C.
Woolwich
Woolwich is a district in southeast London, England, historically significant as a military and industrial hub along the River Thames.
-
D.
Uxbridge
Uxbridge is a township in Ontario, Canada, known for its rural landscapes, trail networks, and proximity to protected natural areas.
-
E.
Uxbridge
Uxbridge is a suburban town in West London, England, known as a major commercial and administrative centre and the terminus of a branch of the London Underground.
- 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_69a88917935081909b755dbf38e81024 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abc6c9396081908abb2b0a229bb046 |
completed | March 7, 2026, 6:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aea88113988190b89abfc01f5bf6f4 |
completed | March 9, 2026, 11:01 a.m. |
Created at: March 4, 2026, 7:52 p.m.