Triple

T13307400
Position Surface form Disambiguated ID Type / Status
Subject Kithairon E316970 entity
Predicate associatedDeity P1481 FINISHED
Object Pan E19364 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: Pan | Statement: [Kithairon, associatedDeity, Pan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pan
Context triple: [Kithairon, associatedDeity, Pan]
  • A. Pan
    Pan is a genus of great apes that includes chimpanzees and bonobos, our closest living evolutionary relatives.
  • B. Pan
    Pan is a 1894 novel by Norwegian author Knut Hamsun, known for its lyrical portrayal of nature and its psychologically intense depiction of love and jealousy.
  • C. Pan chosen
    Pan is the rustic Greek god of shepherds, flocks, and wild nature, often depicted with goat-like features and associated with music and untamed wilderness.
  • D. Pag
    Pag is a Croatian Adriatic island known for its barren, moonlike landscape, distinctive sheep’s milk cheese, and historic lace-making tradition.
  • E. Panenka
    Panenka is a famous football penalty-taking technique in which the kicker delicately chips the ball down the center of the goal, typically as the goalkeeper dives to one side.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990a8be108190bad0021f95ce3a93 completed April 11, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69f71f2810a881908b1ed0cc4fb9ac12 completed May 3, 2026, 10:10 a.m.
Created at: April 9, 2026, 9:29 p.m.