Triple

T10391375
Position Surface form Disambiguated ID Type / Status
Subject Batman: Arkham Asylum E244898 entity
Predicate containsCharacter P5716 FINISHED
Object Scarecrow E225271 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: Scarecrow | Statement: [Batman: Arkham Asylum, containsCharacter, Scarecrow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Scarecrow
Context triple: [Batman: Arkham Asylum, containsCharacter, Scarecrow]
  • A. Scarecrow chosen
    Scarecrow is a Batman supervillain and deranged psychiatrist who uses fear-inducing toxins to terrorize Gotham City.
  • 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. The Scarecrow
    The Scarecrow is a beloved fictional figure from L. Frank Baum’s Oz stories, known for his quest for a brain and his role as one of Dorothy’s loyal companions.
  • D. The Scarecrow
    The Scarecrow is a crime novel by Michael Connelly featuring journalist Jack McEvoy investigating a serial killer who exploits digital technology to stalk his victims.
  • E. Toyman
    Toyman is a DC Comics supervillain known for using deadly toy-themed gadgets and elaborate traps to battle Superman in Metropolis.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9b5b43081908641a5abfb08dc2b completed April 7, 2026, 11:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69d795b9974c819087340adc3622279e completed April 9, 2026, 12:04 p.m.
Created at: April 6, 2026, 12:06 p.m.