Triple

T16099788
Position Surface form Disambiguated ID Type / Status
Subject Haskell Wexler E390584 entity
Predicate notableWork P4 FINISHED
Object Medium Cool E121553 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: Medium Cool | Statement: [Haskell Wexler, notableWork, Medium Cool]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Medium Cool
Context triple: [Haskell Wexler, notableWork, Medium Cool]
  • A. Medium Cool chosen
    Medium Cool is a 1969 American drama film directed by Haskell Wexler that blends fiction and documentary techniques to depict social and political unrest surrounding the 1968 Democratic National Convention in Chicago.
  • B. Medium
    Medium is an online publishing platform that allows writers and readers to share and discover long-form articles, essays, and stories across a wide range of topics.
  • C. Medium
    Medium is a supernatural drama television series centered on a woman who uses her psychic abilities to help solve crimes.
  • D. Tiepido
    Tiepido is a small river in northern Italy that serves as a tributary of the Panaro River.
  • E. Sedang
    Sedang is an Austroasiatic language of the Bahnaric branch spoken by the Sedang people in Vietnam’s Central Highlands.
  • 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_69d87f198bc48190a8b7e53ca15b7ead completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1ff6756948190a7f5ecb375e59701 completed April 17, 2026, 9:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb9d6140819087f9b3dc549c4aec completed May 10, 2026, 2:21 a.m.
Created at: April 10, 2026, 5 a.m.