Triple

T4484880
Position Surface form Disambiguated ID Type / Status
Subject Star Trek: Discovery E107210 entity
Predicate mainCharacter P1183 FINISHED
Object Paul Stamets E238134 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: Paul Stamets | Statement: [Star Trek: Discovery, mainCharacter, Paul Stamets]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul Stamets
Context triple: [Star Trek: Discovery, mainCharacter, Paul Stamets]
  • A. Paul Stamets chosen
    Paul Stamets is an American mycologist, author, and advocate for the study and use of fungi in medicine, ecology, and environmental restoration.
  • B. Dennis McKenna
    Dennis McKenna is an American ethnopharmacologist, author, and researcher known for his work on psychoactive plants and his collaborations with his brother Terence McKenna in the study of psychedelics.
  • C. Michael T. Sauer
    Michael T. Sauer was an American judge best known for presiding over high-profile criminal cases in Los Angeles County.
  • D. Paul Grilley
    Paul Grilley is a yoga teacher best known for popularizing Yin Yoga and for his influential work on anatomy and skeletal variation in yoga practice.
  • E. Robert Krasny
    Robert Krasny is an American applied mathematician known for his work in fluid dynamics and vortex methods.
  • 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_69bd43f84f788190a1383579c4a595be completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd52a758f48190b6b59ca0d9207c2a completed March 20, 2026, 1:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd56ada9508190ab5566490c527d3f completed March 20, 2026, 2:16 p.m.
Created at: March 20, 2026, 12:59 p.m.