Triple
T15113548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tulse Hill railway station |
E360975
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Tulse Hill |
E360975
|
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: Tulse Hill | Statement: [Tulse Hill railway station, locatedIn, Tulse Hill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tulse Hill Context triple: [Tulse Hill railway station, locatedIn, Tulse Hill]
-
A.
Tulse Hill
chosen
Tulse Hill is a residential district in south London known for its diverse community, Victorian housing, and rail links into central London.
-
B.
Turnham Green
Turnham Green is an area in west London, England, known historically as a village green and now as a residential district within the London Borough of Hounslow.
-
C.
Brighton Hill
Brighton Hill is a residential suburb and local community area within the town of Basingstoke in Hampshire, England.
-
D.
Haddon Heights
Haddon Heights is a small suburban borough in southern New Jersey known for its historic homes, tree-lined streets, and close-knit community.
-
E.
Greenhills
Greenhills is a major commercial and shopping complex in San Juan, Metro Manila, known for its vast array of retail stalls, bargain goods, and electronics.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0058d786c8190937c6819255c01bd |
completed | April 15, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7eccb988190aae27dd28cf50997 |
completed | May 9, 2026, 4:28 a.m. |
Created at: April 10, 2026, 3:05 a.m.