Triple

T8508191
Position Surface form Disambiguated ID Type / Status
Subject Orange County Line E201387 entity
Predicate connectsCity P4245 FINISHED
Object Orange E460547 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: Orange | Statement: [Orange County Line, connectsCity, Orange]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orange
Context triple: [Orange County Line, connectsCity, Orange]
  • A. Orange
    Orange is a major French multinational telecommunications company providing mobile, internet, and other digital services across numerous countries.
  • B. Orange
    Orange is a historic town in southeastern France best known for giving its name and origin to the Dutch royal House of Orange-Nassau.
  • C. Orange
    Orange is a citrus-flavored sports drink variety known for its bright, tangy taste and association with energy and hydration.
  • D. Orange chosen
    Orange is a small town in north-central Massachusetts known for its rural character, historic mill village roots, and location along the Millers River.
  • E. Orange
    Orange is a common English surname of likely Norman or French origin, shared by various individuals including the British singer Jason Orange.
  • 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_69ca8320e5748190ac2c585a0bba8193 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe5df74e8819086b1445cc907e371 completed March 31, 2026, 3:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4e37b0548190908632fd167efac1 completed April 2, 2026, 11:08 a.m.
Created at: March 30, 2026, 6:15 p.m.