Triple

T11315530
Position Surface form Disambiguated ID Type / Status
Subject Black Widows E267955 entity
Predicate hasMember P10 FINISHED
Object Ingrid E108797 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: Ingrid | Statement: [Black Widows, hasMember, Ingrid]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ingrid
Context triple: [Black Widows, hasMember, Ingrid]
  • A. Ingrid chosen
    Ingrid is a feminine given name of Scandinavian origin that has been borne by several notable figures, including the Swedish actress Ingrid Bergman.
  • B. INGRID
    INGRID is a near detector of the T2K long-baseline neutrino experiment, designed to monitor the neutrino beam’s direction and intensity.
  • C. Ingeborg
    Ingeborg is a feminine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
  • D. Inger
    Inger is a central female character in Knut Hamsun’s novel "Growth of the Soil," representing the hardships and moral complexities of rural Norwegian life.
  • E. Nina
    Nina is a feminine given name used in various cultures, often as a short form of names like Antonina or Giannina, and borne by numerous notable figures in the arts and public life.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9c2c7b081909af8acebc8aa93aa completed April 9, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69e50a9e66588190b71e0f60133a8995 completed April 19, 2026, 5:02 p.m.
Created at: April 8, 2026, 9:32 p.m.