Triple

T18350217
Position Surface form Disambiguated ID Type / Status
Subject AS Muret E439646 entity
Predicate shortName P43 FINISHED
Object AS Muret NE NERFINISHED

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: AS Muret | Statement: [AS Muret, shortName, AS Muret]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AS Muret
Context triple: [AS Muret, shortName, AS Muret]
  • A. AS Muret chosen
    AS Muret is a French sports club based in the town of Muret, best known for its football team competing in the lower tiers of the national league system.
  • B. Murillo
    Murillo was a prominent 17th-century Spanish Baroque painter renowned for his religious works and tender, luminous depictions of everyday life.
  • C. Murillo
    Murillo is a small rural community located within the Municipality of Oliver Paipoonge in northwestern Ontario, Canada.
  • D. Murillo
    Murillo is a small Colombian town in the Tolima department, known as a gateway for trekking and mountaineering in the Los Nevados National Natural Park.
  • E. Signorelli
    Signorelli is an Italian surname most famously associated with Renaissance painter Luca Signorelli, known for his dramatic frescoes and anatomical precision.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b918221c8190a9f7b563d64ac677 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e514f7700c8190ae220de870e69304 completed April 19, 2026, 5:46 p.m.
Created at: April 10, 2026, 10:37 a.m.