Triple

T11605025
Position Surface form Disambiguated ID Type / Status
Subject Claude, Duke of Guise E275233 entity
Predicate title P38 FINISHED
Object Count of Guise E686937 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: Count of Guise | Statement: [Claude, Duke of Guise, title, Count of Guise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Count of Guise
Context triple: [Claude, Duke of Guise, title, Count of Guise]
  • A. Count of Guise chosen
    The Count of Guise was a noble title in the French aristocracy historically associated with a prominent cadet branch of the House of Lorraine that played a major role in French politics and religious conflicts.
  • B. Count of Blois
    The Count of Blois was a medieval French noble title associated with the powerful lords who ruled the strategically important county of Blois in central France.
  • C. Guise
    Guise is a commune in northern France known for its historic Château de Guise and its role in regional medieval and early modern history.
  • D. Chevaleret
    Chevaleret is a Paris Métro station in the 13th arrondissement, located on the elevated section of Line 6 near the Seine.
  • E. Chevalier de Paris
    Chevalier de Paris was a notable French performer and entertainer associated with the famed Parisian music hall scene.
  • 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_69d6aaf84b548190ac072e4fb89ae18f completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d895502e0081909ee9c3d45d26cd91 completed April 10, 2026, 6:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee87077d008190874a8339b64dd5ec completed April 26, 2026, 9:43 p.m.
Created at: April 8, 2026, 9:38 p.m.