Triple

T3376930
Position Surface form Disambiguated ID Type / Status
Subject Oxford Hills region E71086 entity
Predicate hasTown P847 FINISHED
Object Paris, Maine E45438 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: Paris, Maine | Statement: [Oxford Hills region, hasTown, Paris, Maine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris, Maine
Context triple: [Oxford Hills region, hasTown, Paris, Maine]
  • A. Paris, Maine chosen
    Paris, Maine is a small town in western Maine that serves as the administrative and commercial center of Oxford County.
  • B. Springfield, Maine
    Springfield, Maine is a small rural town located in Penobscot County in eastern Maine, known for its forested landscape and quiet, sparsely populated setting.
  • C. Cambridge, Maine
    Cambridge, Maine is a small rural town in central Maine known for its quiet, forested landscape and location within Somerset County.
  • D. Farmington, Maine
    Farmington, Maine is a small town in western Maine that serves as the service and cultural center of Franklin County and is home to the University of Maine at Farmington.
  • E. Madison, Maine
    Madison, Maine is a small town in central Maine known for its rural character, historic mill industry, and location along the Kennebec River.
  • 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_69ad85a7f80c8190a05e43013f298942 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb2e8d1988190b6fb6c4c5502f25f completed March 8, 2026, 5:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69b334490bf08190aa119e72d12f5e4b completed March 12, 2026, 9:46 p.m.
Created at: March 8, 2026, 3:13 p.m.