Triple

T12893277
Position Surface form Disambiguated ID Type / Status
Subject David Moscow as young Josh Baskin E308421 entity
Predicate ageDepictionConsistency P107302 FINISHED
Object matchesAdultJoshPersonalityTraits 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: matchesAdultJoshPersonalityTraits | Statement: [David Moscow as young Josh Baskin, ageDepictionConsistency, matchesAdultJoshPersonalityTraits]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: ageDepictionConsistency
Context triple: [David Moscow as young Josh Baskin, ageDepictionConsistency, matchesAdultJoshPersonalityTraits]
  • A. portraysAgeGroup
    Indicates that one entity depicts or represents another entity as belonging to a particular age group.
  • B. representedAgeLevel
    Indicates that one entity corresponds to, or is categorized under, a particular age level or age group.
  • C. containsAge
    Indicates that one entity includes or specifies the age value or age-related information of another entity.
  • D. existsInAge
    Indicates that an entity is present, valid, or active during a specified age or time period.
  • E. characterAgeDescriptor
    Indicates how a character’s age is qualitatively described or categorized (e.g., young, middle-aged, elderly) rather than given as a specific number.
  • F. None of above. chosen

Provenance (4 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_69d7bdf7c1f0819098102569a8d8cbf5 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d971484aa08190a8adfafabe600903 completed April 10, 2026, 9:53 p.m.
PD Predicate disambiguation batch_69d96fa776648190b9b5c30722ea50b6 completed April 10, 2026, 9:46 p.m.
PDg Predicate description generation batch_69d9713e45a88190acd346f066093550 completed April 10, 2026, 9:53 p.m.
Created at: April 9, 2026, 5:40 p.m.