Triple

T13015899
Position Surface form Disambiguated ID Type / Status
Subject École de Nancy E322550 entity
Predicate locatedIn P40 FINISHED
Object Nancy E78951 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: Nancy | Statement: [École de Nancy, locatedIn, Nancy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nancy
Context triple: [École de Nancy, locatedIn, Nancy]
  • A. Nancy
    Nancy is a feminine given name of Hebrew origin meaning "grace" that became especially popular in English-speaking countries in the 20th century.
  • B. Nancy chosen
    Nancy is a historic city in northeastern France renowned for its elegant 18th-century architecture and UNESCO-listed Place Stanislas.
  • C. Nance
    Nance is a recurring character on the sketch comedy series "Portlandia," known as one half of the feminist bookstore duo alongside Candace.
  • D. Nance
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • E. Nance
    Nance is a member of the elite military unit J-Squad in the science fiction film "Edge of Tomorrow."
  • 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_69d807657e8c8190bd9435ee2f823845 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97ecd04748190ade2530ee5db35fe completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c0dace788190bf2663984801f38c completed May 3, 2026, 3:28 a.m.
Created at: April 9, 2026, 8:50 p.m.