Triple
T13783961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cross Insurance Center |
E331205
|
entity |
| Predicate | owner |
P347
|
FINISHED |
| Object |
City of Bangor
The City of Bangor is a municipality in Maine that serves as a regional economic, cultural, and service hub for the surrounding area.
|
E1060998
|
NE FINISHED |
How this triple was built (4 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: City of Bangor | Statement: [Cross Insurance Center, owner, City of Bangor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Bangor Context triple: [Cross Insurance Center, owner, City of Bangor]
-
A.
Bangor
Bangor is a coastal town in Northern Ireland known for its marina, seaside resort heritage, and role as a commuter hub for nearby Belfast.
-
B.
Bangor
Bangor is a historic cathedral city in northwest Wales, known for its university and scenic location near the Menai Strait.
-
C.
Bangor
Bangor is a coastal commune located on Belle-Île, an island off the coast of Brittany in northwestern France.
-
D.
BANGOR
BANGOR is a coastal town in County Down, Northern Ireland, known as a seaside resort and commuter town for Belfast.
-
E.
Bangor metropolitan area
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.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: City of Bangor Triple: [Cross Insurance Center, owner, City of Bangor]
Generated description
The City of Bangor is a municipality in Maine that serves as a regional economic, cultural, and service hub for the surrounding area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: City of Bangor Target entity description: The City of Bangor is a municipality in Maine that serves as a regional economic, cultural, and service hub for the surrounding area.
-
A.
Bangor
Bangor is a coastal town in Northern Ireland known for its marina, seaside resort heritage, and role as a commuter hub for nearby Belfast.
-
B.
Bangor
Bangor is a historic cathedral city in northwest Wales, known for its university and scenic location near the Menai Strait.
-
C.
Bangor
Bangor is a coastal commune located on Belle-Île, an island off the coast of Brittany in northwestern France.
-
D.
BANGOR
BANGOR is a coastal town in County Down, Northern Ireland, known as a seaside resort and commuter town for Belfast.
-
E.
Bangor metropolitan area
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.
- F. None of above. chosen
Provenance (5 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_69d81c58feb08190a77bca8bf7d6d20f |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0247ccc881908dad7b547221f15d |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b07b0b2881909b316e3cc67f1ec1 |
completed | May 3, 2026, 8:30 p.m. |
| NEDg | Description generation | batch_69f7b138158c8190957d43d529c37fa4 |
completed | May 3, 2026, 8:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7b1e2e1b481908b74b5053e49fa38 |
completed | May 3, 2026, 8:36 p.m. |
Created at: April 9, 2026, 10:11 p.m.