Triple

T485920
Position Surface form Disambiguated ID Type / Status
Subject Province V E9876 entity
Predicate alsoKnownAs P39 FINISHED
Object Province Five E9478 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: Province Five | Statement: [Province V, alsoKnownAs, Province Five]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Province Five
Context triple: [Province V, alsoKnownAs, Province Five]
  • A. Province 5
    Province 5 is one of the administrative provinces of Nepal, located in the western part of the country and known for its diverse geography and cultural heritage.
  • B. Province IV chosen
    Province IV is one of the regional ecclesiastical provinces of the Episcopal Church in the United States, encompassing dioceses primarily in the southeastern part of the country.
  • C. River City
    River City is a popular nickname for Richmond, Virginia, highlighting the city's location along the James River and its historic riverfront character.
  • D. River City
    River City is a popular nickname for Sacramento, California, highlighting the city’s close connection to the nearby American and Sacramento Rivers.
  • E. River City
    River City is a popular nickname for Wuhan, a major central Chinese metropolis known for its location at the confluence of the Yangtze and Han rivers.
  • 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_69a2e802e2908190ab17c9479e0b6412 completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2f0bc6f548190b13dee42cb100423 completed Feb. 28, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69a474701340819096a5073155af9625 completed March 1, 2026, 5:16 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.