Triple

T20299386
Position Surface form Disambiguated ID Type / Status
Subject MS 3501 E505437 entity
Predicate contains P35 FINISHED
Object The Panther 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: The Panther | Statement: [MS 3501, contains, The Panther]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Panther
Context triple: [MS 3501, contains, The Panther]
  • A. The Panther chosen
    The Panther is a medieval literary work, likely a poem or text, that survives in the same manuscript as "The Gifts of Men."
  • B. Panther
    The Panther is the fierce and agile feline mascot representing Clark Atlanta University’s athletic teams and school spirit.
  • C. Panther
    Panther is the codename for Mac OS X 10.3, a major early-2000s release of Apple’s Mac operating system known for performance improvements and new user interface features.
  • D. Panther
    Panther is the nickname of the German professional ice hockey club ERC Ingolstadt, reflecting the team's fierce and dynamic identity.
  • E. Panther
    Panther is the NATO reporting name for the German World War II medium tank Panzerkampfwagen V, renowned for its powerful gun, sloped armor, and significant impact on armored warfare.
  • 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_69e0b4b8ab648190906e18538c250148 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6770b9484819090ffcb339f2a435a completed April 20, 2026, 6:57 p.m.
Created at: April 16, 2026, 11:16 a.m.