Triple
T11260184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bethesda, Gwynedd |
E266540
|
entity |
| Predicate | postalTown |
P2711
|
FINISHED |
| Object | BANGOR |
E843200
|
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: BANGOR | Statement: [Bethesda, Gwynedd, postalTown, BANGOR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BANGOR Context triple: [Bethesda, Gwynedd, postalTown, BANGOR]
-
A.
BANGOR
chosen
BANGOR is a coastal town in County Down, Northern Ireland, known as a seaside resort and commuter town for Belfast.
-
B.
Bangor, Maine
Bangor, Maine is a small city in eastern Maine known as a regional commercial and cultural hub and famously associated with author Stephen King.
-
C.
Belfast, Maine
Belfast, Maine is a small coastal city in the Midcoast region known for its historic downtown, arts community, and harbor on Penobscot Bay.
-
D.
Biddeford, Maine
Biddeford, Maine is a historic mill city in York County known for its revitalized downtown along the Saco River and its role as a regional economic and educational center.
-
E.
Portland, Maine
Portland, Maine is a coastal New England city known for its historic Old Port district, vibrant arts and food scenes, and working waterfront on Casco Bay.
- 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_69d6aac7953c8190b82caf9d7640fdf9 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e936cb048190b4d6fb2851ef8932 |
completed | April 9, 2026, 6 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4f410cb508190bb0ceab51075eec5 |
completed | April 19, 2026, 3:26 p.m. |
Created at: April 8, 2026, 9:31 p.m.