Triple

T7803109
Position Surface form Disambiguated ID Type / Status
Subject Antoinette Alberdingk Thijm E180479 entity
Predicate givenName P17 FINISHED
Object Antoinette E182168 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: Antoinette | Statement: [Antoinette Alberdingk Thijm, givenName, Antoinette]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Antoinette
Context triple: [Antoinette Alberdingk Thijm, givenName, Antoinette]
  • A. Antoinette
    Antoinette is the birth name of Princess Muna al-Hussein, the British-born mother of King Abdullah II of Jordan.
  • B. Antoinette chosen
    Antoinette is a feminine given name of French origin, historically associated with nobility and later borne by various notable figures in the arts and public life.
  • C. Renée
    Renée is a feminine given name of French origin, commonly used in French-speaking countries and beyond.
  • D. Arlette
    Arlette, also known as Herleva of Falaise, was the mother of William the Conqueror and a key figure in the early life of the first Norman king of England.
  • E. Armande
    Armande is a French given name historically associated with figures in the performing arts, notably in 17th-century France.
  • 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_69ca827e50cc8190a92a733577184938 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69caf635a4648190af907a686d87f073 completed March 30, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb14371e2081908d0a798d3b785c3c completed March 31, 2026, 12:24 a.m.
Created at: March 30, 2026, 4:34 p.m.