Triple

T6471714
Position Surface form Disambiguated ID Type / Status
Subject Fulk V of Anjou E142367 entity
Predicate title P38 FINISHED
Object Count of Maine E430348 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: Count of Maine | Statement: [Fulk V of Anjou, title, Count of Maine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Count of Maine
Context triple: [Fulk V of Anjou, title, Count of Maine]
  • A. Count of Maine chosen
    The Count of Maine was a medieval French noble title associated with the strategically important province of Maine, often held by powerful royal and princely figures such as Charles I of Anjou.
  • B. Rockland, Maine
    Rockland, Maine is a coastal city in midcoast Maine known for its busy harbor, maritime industries, and role as a transportation and cultural hub for the region.
  • C. Freedom, Maine
    Freedom, Maine is a small rural town in central Maine known for its scenic countryside and tight-knit community.
  • D. Gray, Maine
    Gray, Maine is a small New England town in southern Maine known for its rural character, proximity to Portland, and the Maine Wildlife Park.
  • E. Levant, Maine
    Levant, Maine is a small rural town located in Penobscot County in central Maine, known for its agricultural character and close proximity to the city of Bangor.
  • 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_69c008d3bf4c8190bcf798c5ba9d6fb3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06a2fd4248190a789bf0301e2860a completed March 22, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84ece7e2881909da0e81ccf8c4eb4 completed March 28, 2026, 9:57 p.m.
Created at: March 22, 2026, 4:50 p.m.