Triple

T19685978
Position Surface form Disambiguated ID Type / Status
Subject ESO 324-G024 E472711 entity
Predicate hasIrregular P27380 FINISHED
Object morphology 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: morphology | Statement: [ESO 324-G024, hasIrregular, morphology]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasIrregular
Context triple: [ESO 324-G024, hasIrregular, morphology]
  • A. hasIrregularShape chosen
    Indicates that an entity possesses a form or outline that deviates from a regular, standard, or symmetrical shape.
  • B. meetsIrregularly
    Indicates that two or more entities come together or interact on a non-fixed, inconsistent, or unpredictable schedule.
  • C. hasRegularity
    Indicates that one entity exhibits a consistent, recurring pattern or uniform behavior with respect to another entity or over time.
  • D. areRegularIn
    Indicates that entities participate in or occur within a context, pattern, or structure in a consistent, uniform, and rule-governed manner.
  • E. hadIrregularMonthLengths
    Indicates that the calendar system in question used months whose lengths were not uniform or consistently patterned across the year.
  • 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_69d8e515bef88190bc30781aea50537a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e641c33b94819081bdeb56910f6ff8 completed April 20, 2026, 3:09 p.m.
PD Predicate disambiguation batch_69e53039ea808190a9106a53f564ab92 completed April 19, 2026, 7:42 p.m.
Created at: April 10, 2026, 1:45 p.m.