Triple
T853686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bangor, Maine |
E18442
|
entity |
| Predicate | metropolitanArea |
P294
|
FINISHED |
| Object | Bangor metropolitan area |
E7564
|
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 metropolitan area | Statement: [Bangor, Maine, metropolitanArea, Bangor metropolitan area]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bangor metropolitan area Context triple: [Bangor, Maine, metropolitanArea, Bangor metropolitan area]
-
A.
Bangor metropolitan area
chosen
The Bangor metropolitan area is a regional urban and economic hub in central-eastern Maine centered on the city of Bangor and its surrounding communities.
-
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.
Haverhill
Haverhill is a historic city in northeastern Massachusetts that functions as a suburban community within the Greater Boston metropolitan area.
-
D.
Stafford
Stafford is a county in Northern Virginia known for its suburban communities, historical sites, and proximity to Washington, D.C.
-
E.
Oxford Hills region
The Oxford Hills region is an area of western Maine known for its small towns, outdoor recreation, and proximity to the White Mountains.
- 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_69a4938bdd3c8190a954a3c11844d9cf |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac389a44819093396a58d2afa700 |
completed | March 1, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7a3bd8b588190b7a9eb72dce93d07 |
completed | March 4, 2026, 3:15 a.m. |
Created at: March 1, 2026, 7:39 p.m.