Triple

T10707533
Position Surface form Disambiguated ID Type / Status
Subject Claude of France E252445 entity
Predicate givenName P17 FINISHED
Object Claude E1167 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: Claude | Statement: [Claude of France, givenName, Claude]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Claude
Context triple: [Claude of France, givenName, 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. Anthropic Claude
    Anthropic Claude is an advanced AI assistant developed by Anthropic, designed to provide helpful, honest, and safe natural language interactions.
  • C. Ray Tune
    Ray Tune is a scalable hyperparameter tuning and experiment management library for machine learning, built on the Ray distributed computing framework.
  • D. Claudy
    Claudy is a small village and townland in County Londonderry, Northern Ireland, situated near the River Faughan and known for its rural setting and local community.
  • E. Blaise
    The Blaise is a small river in northern France that flows through the Eure department as one of its tributaries.
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fde080d48190830eaa863aad61ff completed April 9, 2026, 1:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d9990760b48190a05753974cdf556c completed April 11, 2026, 12:42 a.m.
Created at: April 8, 2026, 9:12 p.m.