Triple

T4383183
Position Surface form Disambiguated ID Type / Status
Subject Hollywood Casino Bangor E99177 entity
Predicate near P350 FINISHED
Object Downtown Bangor E18442 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: Downtown Bangor | Statement: [Hollywood Casino Bangor, near, Downtown Bangor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Downtown Bangor
Context triple: [Hollywood Casino Bangor, near, Downtown Bangor]
  • A. Bangor, Maine chosen
    Bangor, Maine is a small city in eastern Maine known as a regional commercial and cultural hub and famously associated with author Stephen King.
  • B. West End, Portland, Maine
    West End, Portland, Maine is a historic, largely residential neighborhood on the western side of the Portland peninsula, known for its well-preserved 19th-century architecture and scenic views over the Fore River.
  • C. Bangor City Hall
    Bangor City Hall is the historic municipal government building and civic landmark located in downtown Bangor, Maine.
  • D. South Portland, Maine
    South Portland, Maine is a coastal city in Cumberland County known for its industrial base, retail centers, and proximity to Portland Harbor.
  • E. 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.
  • 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_69b3454ea8f48190a49c2436624d6ef6 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35262649c8190a724c9835cb7ece6 completed March 12, 2026, 11:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e523cc5c8190b9884f83d433982c completed March 14, 2026, 10:45 p.m.
Created at: March 12, 2026, 11:18 p.m.