Triple

T23540895
Position Surface form Disambiguated ID Type / Status
Subject Daniel Licht E577742 entity
Predicate composedFor P30143 FINISHED
Object Thinner 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: Thinner | Statement: [Daniel Licht, composedFor, Thinner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thinner
Context triple: [Daniel Licht, composedFor, Thinner]
  • A. Thinner chosen
    Thinner is a 1996 horror film based on Stephen King’s novel of the same name, following a cursed lawyer who rapidly and uncontrollably loses weight after a hit-and-run accident.
  • B. Thinner (novel)
    Thinner (novel) is a 1984 horror book by Stephen King (writing as Richard Bachman) about an obese lawyer cursed to rapidly lose weight after a hit-and-run accident.
  • C. Thick & Thin
    "Thick & Thin" is a song featured on the album "Unrequited."
  • D. Thins
    Thins is a Dutch family name historically associated with Maria Thins, the wealthy Delft patron and mother-in-law of painter Johannes Vermeer.
  • E. Fat Lip
    "Fat Lip" is a 2001 breakout single by Canadian rock band Sum 41 that blends pop-punk and rap elements and became one of their most recognizable hits.
  • 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_69e245f9d5d08190a4a20004e1784e20 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1ae1b3a8c8190b5b6a58f0476c5d2 completed April 29, 2026, 7:07 a.m.
Created at: April 17, 2026, 6:10 p.m.