Triple

T37980099
Position Surface form Disambiguated ID Type / Status
Subject Tauja Catchings E947527 entity
Predicate sexOrGender P72 FINISHED
Object female LITERAL FINISHED

How this triple was built (1 step)

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: female | Statement: [Tauja Catchings, sexOrGender, female]

Provenance (2 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_69f76ef8a1d08190a741bbbc5970e3b3 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbc8f29aa08190a88a3d7847071457 completed May 6, 2026, 11:04 p.m.
Created at: May 3, 2026, 4:20 p.m.