Triple

T16623739
Position Surface form Disambiguated ID Type / Status
Subject Secret Society E403893 entity
Predicate hasMember P10 FINISHED
Object Toyman E733571 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: Toyman | Statement: [Secret Society, hasMember, Toyman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toyman
Context triple: [Secret Society, hasMember, Toyman]
  • A. Toyman chosen
    Toyman is a DC Comics supervillain known for using deadly toy-themed gadgets and elaborate traps to battle Superman in Metropolis.
  • B. Scarecrow
    Scarecrow is a 1973 American road drama film directed by Jerry Schatzberg and starring Gene Hackman and Al Pacino as drifters traveling across the United States.
  • C. Scarecrow
    Scarecrow is a 1985 heartland rock album by John Mellencamp that blends socially conscious lyrics with a rootsy, Americana sound.
  • D. Scarecrow
    Scarecrow is a Batman supervillain and deranged psychiatrist who uses fear-inducing toxins to terrorize Gotham City.
  • E. Scarecrow
    Scarecrow is a beloved character from L. Frank Baum’s Oz series, known for traveling with Dorothy to see the Wizard in hopes of gaining a brain despite already showing wisdom and kindness.
  • 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_69d883897eb481909eaaa088ba9918d9 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37550ee308190931fd50aeebe1e7e completed April 18, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a007db866e48190886aec7658835543 completed May 10, 2026, 12:44 p.m.
Created at: April 10, 2026, 5:17 a.m.