Triple

T278713
Position Surface form Disambiguated ID Type / Status
Subject Lady Blanche Hozier E5306 entity
Predicate givenName P17 FINISHED
Object Blanche
Blanche is a feminine given name of French origin historically associated with nobility and literary figures.
 E36272 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: Blanche | Statement: [Lady Blanche Hozier, givenName, Blanche]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Blanche
Context triple: [Lady Blanche Hozier, givenName, Blanche]
  • A. Lucille
    "Lucille" is a 1977 country song by Kenny Rogers that became one of his signature hits and a classic of the genre.
  • B. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • C. Louise
    Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
  • D. Estelle
    Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
  • E. Tessie
    Tessie is a Boston Red Sox mascot character, often depicted as a green monster and associated with Wally the Green Monster.
  • 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: Blanche
Triple: [Lady Blanche Hozier, givenName, Blanche]
Generated description
Blanche is a feminine given name of French origin historically associated with nobility and literary figures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Blanche
Target entity description: Blanche is a feminine given name of French origin historically associated with nobility and literary figures.
  • A. Lucille
    "Lucille" is a 1977 country song by Kenny Rogers that became one of his signature hits and a classic of the genre.
  • B. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • C. Louise
    Louise is a feminine given name of French origin, traditionally associated with nobility and widely used in many European and English-speaking countries.
  • D. Estelle
    Estelle is a British singer, rapper, and songwriter best known for her hit single "American Boy" featuring Kanye West.
  • E. Tessie
    Tessie is a Boston Red Sox mascot character, often depicted as a green monster and associated with Wally the Green Monster.
  • 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_69a257e6c8788190987dfe705ca2912a completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25dee7830819087f153769a8496b9 completed Feb. 28, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69a394a2b1a081909bb78499544984da completed March 1, 2026, 1:21 a.m.
NEDg Description generation batch_69a3956f12208190bdfc4f265b712ce8 completed March 1, 2026, 1:25 a.m.
NED2 Entity disambiguation (via description) batch_69a395e03da8819095339cc6f9a230e4 completed March 1, 2026, 1:26 a.m.
Created at: Feb. 28, 2026, 2:59 a.m.