Triple
T21871377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Accrington railway station |
E540008
|
entity |
| Predicate | servedPlace |
P3936
|
FINISHED |
| Object | Halifax |
—
|
NE NERFINISHED |
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: Halifax | Statement: [Accrington railway station, servedPlace, Halifax]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Halifax Context triple: [Accrington railway station, servedPlace, Halifax]
-
A.
Halifax
Halifax is the capital city of the Canadian province of Nova Scotia, known as a major Atlantic port and regional economic and cultural center.
-
B.
Halifax
Halifax is a small town in Plymouth County, Massachusetts, known for its residential character and proximity to numerous lakes and conservation areas.
-
C.
Halifax
Halifax is a major UK retail bank known for offering personal banking, mortgages, and savings products.
-
D.
Halifax
Halifax was a British four‑engined heavy bomber aircraft widely used by the Royal Air Force during World War II.
-
E.
Halifax
chosen
Halifax is a historic industrial town in West Yorkshire, England, known for its textile heritage and distinctive Victorian architecture.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c478f59081909d54302b57fc1ce3 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0f3368d488190a37224b587858ab0 |
completed | April 28, 2026, 5:49 p.m. |
Created at: April 16, 2026, 6:57 p.m.