Triple

T36205849
Position Surface form Disambiguated ID Type / Status
Subject Grand Huntsman E1047394 entity
Predicate correspondingFrenchTitle P7000 FINISHED
Object Grand Veneur
Grand Veneur is the French court title historically given to the chief royal huntsman responsible for organizing and overseeing the monarch’s hunts.
 E2172800 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: Grand Veneur | Statement: [Grand Huntsman, correspondingFrenchTitle, Grand Veneur]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Grand Veneur
Triple: [Grand Huntsman, correspondingFrenchTitle, Grand Veneur]
Generated description
Grand Veneur is the French court title historically given to the chief royal huntsman responsible for organizing and overseeing the monarch’s hunts.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: correspondingFrenchTitle
Context triple: [Grand Huntsman, correspondingFrenchTitle, Grand Veneur]
  • A. equivalentTitleInFrench chosen
    Indicates that one entity’s title is the equivalent or corresponding title of another entity, specifically expressed in French.
  • B. equivalentTitleInLanguage
    Indicates that two titles are equivalent in meaning or reference, but expressed in a specified language.
  • C. titleInLanguage
    Indicates that a specific title or name is expressed in a particular language.
  • D. titleInEnglish
    Indicates that an entity’s title or name is given in the English language.
  • E. equivalentTitleInJapanese
    Indicates that one entity has a corresponding or matching title in Japanese that is equivalent in meaning or usage to the other entity’s title.
  • F. None of above.

Provenance (6 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_69f76e414bdc8190996f15a544220a3d completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f9fd6834cc8190aa27153d6a99f3bb completed May 5, 2026, 2:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3934217e588190aeeaf3a1e21bdaa9 completed June 22, 2026, 1:09 p.m.
NEDg Description generation batch_6a39350a315c8190838fa2987f631da1 completed June 22, 2026, 1:13 p.m.
NED2 Entity disambiguation (via description) batch_6a39356e210c8190badece11b58c96b2 completed June 22, 2026, 1:15 p.m.
PD Predicate disambiguation batch_69f7cf769338819092a5f42653dcc956 completed May 3, 2026, 10:43 p.m.
Created at: May 3, 2026, 4:08 p.m.