Triple

T13783974
Position Surface form Disambiguated ID Type / Status
Subject Cross Insurance Center E331205 entity
Predicate city P40 FINISHED
Object Bangor
Bangor is a small city in central Maine known as a regional commercial hub and cultural center for the surrounding area.
 E7564 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: Bangor | Statement: [Cross Insurance Center, city, Bangor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bangor
Context triple: [Cross Insurance Center, city, Bangor]
  • A. Bangor
    Bangor is a historic cathedral city in northwest Wales, known for its university and scenic location near the Menai Strait.
  • B. 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.
  • C. Bangor
    Bangor is a coastal commune located on Belle-Île, an island off the coast of Brittany in northwestern France.
  • D. 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.
  • E. BANGOR
    BANGOR is a coastal town in County Down, Northern Ireland, known as a seaside resort and commuter town for Belfast.
  • 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: Bangor
Triple: [Cross Insurance Center, city, Bangor]
Generated description
Bangor is a small city in central Maine known as a regional commercial hub and cultural center for the surrounding area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bangor
Target entity description: Bangor is a small city in central Maine known as a regional commercial hub and cultural center for the surrounding area.
  • A. Bangor
    Bangor is a historic cathedral city in northwest Wales, known for its university and scenic location near the Menai Strait.
  • B. 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.
  • C. Bangor
    Bangor is a coastal commune located on Belle-Île, an island off the coast of Brittany in northwestern France.
  • D. 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.
  • E. BANGOR
    BANGOR is a coastal town in County Down, Northern Ireland, known as a seaside resort and commuter town for Belfast.
  • F. None of above.

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_69f7b8d6b3c88190aa8fb72d8ad9644d completed May 3, 2026, 9:06 p.m.
NEDg Description generation batch_69f7b9d773f881908660e8a0645d318d completed May 3, 2026, 9:10 p.m.
NED2 Entity disambiguation (via description) batch_69f7bbf47c888190be32a4105903120a completed May 3, 2026, 9:19 p.m.
Created at: April 9, 2026, 10:11 p.m.