Triple

T14794844
Position Surface form Disambiguated ID Type / Status
Subject Caldas E347746 entity
Predicate hasMunicipality P847 FINISHED
Object Pensilvania E176915 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: Pensilvania | Statement: [Caldas, hasMunicipality, Pensilvania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pensilvania
Context triple: [Caldas, hasMunicipality, Pensilvania]
  • A. Pensilvania chosen
    Pensilvania is a municipality and town located in the Caldas Department of Colombia, known for its coffee-growing economy and mountainous Andean landscape.
  • B. Pennsylvania
    Pennsylvania is a historically significant U.S. state in the Mid-Atlantic and Northeastern regions, known for cities like Philadelphia and Pittsburgh and its central role in the nation’s founding.
  • C. Penn
    Penn is a picturesque village in Buckinghamshire, England, known for its historic church, traditional Chilterns architecture, and scenic countryside setting.
  • D. Penn
    Penn is a private Ivy League research university in Philadelphia known for its strong programs in business, law, medicine, and the liberal arts.
  • E. Penn
    Penn is the stage and given name of Penn Jillette, the outspoken magician, comedian, and half of the famed duo Penn & Teller.
  • 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_69d822ea8b7c819097dfadf3d45545e6 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decd5fdd548190a2ee5e668c2b20b4 completed April 14, 2026, 11:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24bea4408190975f4856cc02580e completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:31 a.m.