Triple

T350629
Position Surface form Disambiguated ID Type / Status
Subject Claudine E7433 entity
Predicate hasMasculineCounterpart P6587 FINISHED
Object Claude E1167 NE FINISHED

How this triple was built (3 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: Claude | Statement: [Claudine, hasMasculineCounterpart, Claude]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Claude
Context triple: [Claudine, hasMasculineCounterpart, Claude]
  • A. Claude chosen
    Claude is a given name most famously associated with Claude Shannon, the American mathematician and electrical engineer known as the father of information theory.
  • B. Michel
    Michel is the birth name of the acclaimed Egyptian actor Omar Sharif, renowned for his roles in classic films such as "Lawrence of Arabia" and "Doctor Zhivago."
  • C. DALL·E
    DALL·E is an AI model developed by OpenAI that generates images from natural language descriptions, enabling text-to-image synthesis.
  • D. André
    André is a given name of French origin commonly used in various languages as a form of "Andrew."
  • E. Jacques
    Jacques is the French form of the given name James, commonly used in French-speaking countries.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasMasculineCounterpart
Context triple: [Claudine, hasMasculineCounterpart, Claude]
  • A. hasFemaleEquivalent
    Indicates that one entity serves as the female counterpart or equivalent of another entity.
  • B. hasGrammaticalGender
    Indicates that one entity assigns or possesses a specific grammatical gender in relation to another entity (such as a word, phrase, or linguistic unit).
  • C. hasNeutralPronoun
    Indicates that an entity is referred to using a gender-neutral pronoun.
  • D. hasPronounForHe
    Indicates that an entity is referred to or can be referred to using the pronoun "he."
  • E. hasCounterpart chosen
    Indicates that one entity corresponds to, matches, or serves as an equivalent or parallel version of another entity.
  • F. None of above.

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_69a2e7e696948190bebc966535995e45 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2eb1f028c819098fa6480b4ca5cf0 completed Feb. 28, 2026, 1:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3e57497948190918b163378036fd4 completed March 1, 2026, 7:06 a.m.
PD Predicate disambiguation batch_69a2e955d1f88190bd687c46fa7c5469 completed Feb. 28, 2026, 1:10 p.m.
Created at: Feb. 28, 2026, 1:08 p.m.