Triple
T16734225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Tottenham |
E406674
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | West Green |
E407795
|
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: West Green | Statement: [South Tottenham, adjacentTo, West Green]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: West Green Context triple: [South Tottenham, adjacentTo, West Green]
-
A.
West Green
chosen
West Green is a residential neighborhood in the London district of Tottenham, known for its diverse community and urban character.
-
B.
West Green
West Green is a residential neighbourhood within the town of Crawley in West Sussex, England.
-
C.
South Green
South Green is a historic central town green in Old Saybrook, Connecticut, around which the Old Saybrook South Green Historic District is organized.
-
D.
South Green
South Green is a historic residential and commercial neighborhood located just south of downtown Hartford, Connecticut.
-
E.
Weston Green
Weston Green is a small suburban area in Surrey, England, situated close to the village of Thames Ditton and within the commuter belt of Greater London.
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e39c38c9cc8190a3220cc3684388dc |
completed | April 18, 2026, 2:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a51c5c388190a88f8bd67dbac82e |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 5:20 a.m.