Triple
T20500869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enniscorthy |
E503297
|
entity |
| Predicate | nearbyTown |
P3883
|
FINISHED |
| Object | Wexford |
—
|
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: Wexford | Statement: [Enniscorthy, nearbyTown, Wexford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wexford Context triple: [Enniscorthy, nearbyTown, Wexford]
-
A.
Wexford
chosen
Wexford is a historic coastal town in County Wexford, Ireland, known for its medieval heritage and role in events such as the 1649 siege during the Cromwellian conquest.
-
B.
Waterford
Waterford is a small town and village in eastern New York State, known as the eastern terminus of the Erie Canal and its historic canal locks.
-
C.
Waterford
Waterford is a small incorporated city located in Stanislaus County in California’s Central Valley.
-
D.
Waterford
Waterford is a historic port city in southeast Ireland, renowned as the country’s oldest city and for its traditional crystal glassmaking.
-
E.
Waterford
Waterford is a small borough in Erie County, Pennsylvania, known for its historic architecture and role in the early development of the region.
- 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_69e0b4b1e52c8190894281cf7e3283ab |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69cc1ea7081908d17c224b1670bd7 |
completed | April 20, 2026, 9:38 p.m. |
Created at: April 16, 2026, 11:35 a.m.