Triple

T10503343
Position Surface form Disambiguated ID Type / Status
Subject Kevin (Sin City) E247724 entity
Predicate enemy P4567 FINISHED
Object Marv E861745 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: Marv | Statement: [Kevin (Sin City), enemy, Marv]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marv
Context triple: [Kevin (Sin City), enemy, Marv]
  • A. Marv
    Marv is an ancient city in present-day Turkmenistan that was a major Silk Road hub and one of the great cultural and commercial centers of the Islamic world.
  • B. Marv chosen
    Marv is a masculine given name, often used as a shortened form of Marvin.
  • C. Marvin
    Marvin is the given first name of Pro Football Hall of Fame coach Marv Levy, known for leading the Buffalo Bills to four consecutive Super Bowl appearances.
  • D. Marvin
    Marvin is a given name most famously associated with Marvin Minsky, a pioneering cognitive scientist and co-founder of the field of artificial intelligence.
  • E. Marvin
    Marvin is a character featured in the musical works of American composer and lyricist William Finn, notably in his "Marvin Trilogy" of shows.
  • 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_69d381c4aa948190942e1d803143fb0e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5099d62408190a6c6884411c6e423 completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8dcd89ba481908653730b43e3d4ab completed April 10, 2026, 11:19 a.m.
Created at: April 6, 2026, 12:25 p.m.