Triple

T11339317
Position Surface form Disambiguated ID Type / Status
Subject InGen E268552 entity
Predicate hasFictionalLegalIssues P4511 FINISHED
Object lawsuits after Jurassic Park incident LITERAL 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: lawsuits after Jurassic Park incident | Statement: [InGen, hasFictionalLegalIssues, lawsuits after Jurassic Park incident]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFictionalLegalIssues
Context triple: [InGen, hasFictionalLegalIssues, lawsuits after Jurassic Park incident]
  • A. hasFictionalIssue
    Indicates that one entity possesses, is associated with, or is characterized by a particular fictional problem, flaw, or complication.
  • B. hasLegalIssue chosen
    Indicates that an entity is involved in, associated with, or subject to a legal problem, dispute, or proceeding.
  • C. hasFictionalWork
    Indicates that one entity is the creator, owner, or source of a fictional work associated with another entity.
  • D. hasFictionalContent
    Indicates that something contains or includes material that is imaginary, invented, or not intended to represent real events or facts.
  • E. hasGroundsInFiction
    Indicates that something is based on, justified by, or finds its origin within fictional works or narratives.
  • F. None of above.

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_69d6aacb1f0881908c84a349fd1be047 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea01c6c08190910a6ce8fb7e186d completed April 9, 2026, 6:03 p.m.
PD Predicate disambiguation batch_69d787afe5a48190b8af1a3e19529641 completed April 9, 2026, 11:04 a.m.
Created at: April 8, 2026, 9:33 p.m.