Triple

T2989459
Position Surface form Disambiguated ID Type / Status
Subject Marshal Tallard E80710 entity
Predicate familyName P18 FINISHED
Object d’Hostun
d’Hostun is a French noble family name historically associated with military leaders such as Marshal Tallard.
 E316253 NE FINISHED

How this triple was built (4 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: d’Hostun | Statement: [Marshal Tallard, familyName, d’Hostun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: d’Hostun
Context triple: [Marshal Tallard, familyName, d’Hostun]
  • A. Gauda
    Gauda was a historic region in eastern India, centered in present-day West Bengal and Bangladesh, that served as an important political and cultural center in early medieval times.
  • B. Dainzú
    Dainzú is an ancient Zapotec archaeological site in Oaxaca, Mexico, notable for its terraced architecture and carved stone reliefs depicting ballgame scenes.
  • C. Doncieux
    Doncieux is a French surname most notably associated with Camille Doncieux, the first wife and frequent model of painter Claude Monet.
  • D. Henreid
    Henreid is the surname of Paul Henreid, the Austrian-born actor and director best known for his roles in classic Hollywood films such as "Casablanca" and "Now, Voyager."
  • E. Balzar
    Balzar is a town and agricultural center in coastal Ecuador, known for its rice and banana production within Guayas Province.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: d’Hostun
Triple: [Marshal Tallard, familyName, d’Hostun]
Generated description
d’Hostun is a French noble family name historically associated with military leaders such as Marshal Tallard.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: d’Hostun
Target entity description: d’Hostun is a French noble family name historically associated with military leaders such as Marshal Tallard.
  • A. Gauda
    Gauda was a historic region in eastern India, centered in present-day West Bengal and Bangladesh, that served as an important political and cultural center in early medieval times.
  • B. Dainzú
    Dainzú is an ancient Zapotec archaeological site in Oaxaca, Mexico, notable for its terraced architecture and carved stone reliefs depicting ballgame scenes.
  • C. Doncieux
    Doncieux is a French surname most notably associated with Camille Doncieux, the first wife and frequent model of painter Claude Monet.
  • D. Henreid
    Henreid is the surname of Paul Henreid, the Austrian-born actor and director best known for his roles in classic Hollywood films such as "Casablanca" and "Now, Voyager."
  • E. Balzar
    Balzar is a town and agricultural center in coastal Ecuador, known for its rice and banana production within Guayas Province.
  • F. None of above. chosen

Provenance (5 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_69ad8b16c3488190b47b6aa7a59a335b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99dcdb00819092ca5f10396408e0 completed March 8, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b10900bf2481908b7742604c6d75e9 completed March 11, 2026, 6:17 a.m.
NEDg Description generation batch_69b10bda5d848190af553c5f245b165d completed March 11, 2026, 6:29 a.m.
NED2 Entity disambiguation (via description) batch_69b10c9198288190a3e3ea7112ea4460 completed March 11, 2026, 6:32 a.m.
Created at: March 8, 2026, 2:59 p.m.