Triple
T14901049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heald Green |
E360003
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Gatley |
E351791
|
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: Gatley | Statement: [Heald Green, adjacentTo, Gatley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gatley Context triple: [Heald Green, adjacentTo, Gatley]
-
A.
Gatley
chosen
Gatley is a suburban village within the Greater Manchester conurbation in North West England.
-
B.
Tyldesley
Tyldesley is a town in Greater Manchester, England, historically part of Lancashire and known for its industrial heritage, particularly in coal mining and textiles.
-
C.
Ferryhill
Ferryhill is a small town in County Durham, England, known historically for its coal mining heritage and location between Durham and Darlington.
-
D.
Honley
Honley is a large village in West Yorkshire, England, situated in the Holme Valley near Huddersfield.
-
E.
Engleby
Engleby is a psychological novel by Sebastian Faulks that follows the unsettling, introspective narrative of a socially isolated Cambridge student who may be involved in a mysterious disappearance.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded609bf68819099ca3aa3fe1acadc |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe72b30c6881908b80ca96fb5b716f |
completed | May 8, 2026, 11:33 p.m. |
Created at: April 10, 2026, 2:11 a.m.