Triple

T1781399
Position Surface form Disambiguated ID Type / Status
Subject Paris Métro Line 4 E39297 entity
Predicate hasStation P35 FINISHED
Object Barbara
Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
 E224907 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: Barbara | Statement: [Paris Métro Line 4, hasStation, Barbara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Barbara
Context triple: [Paris Métro Line 4, hasStation, Barbara]
  • A. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • B. Lucille
    "Lucille" is a 1977 country song by Kenny Rogers that became one of his signature hits and a classic of the genre.
  • C. Lucille
    Lucille is the famous black Gibson guitar closely associated with blues legend B.B. King, who named all his guitars by this name.
  • D. Diane
    Diane is a feminine given name of Latin origin, derived from the name of the Roman goddess Diana.
  • E. Bernice
    Bernice is a feminine given name most notably borne by Bernice King, the daughter of civil rights leaders Martin Luther King Jr. and Coretta Scott King.
  • 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: Barbara
Triple: [Paris Métro Line 4, hasStation, Barbara]
Generated description
Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Barbara
Target entity description: Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
  • A. Barbara
    Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
  • B. Lucille
    "Lucille" is a 1977 country song by Kenny Rogers that became one of his signature hits and a classic of the genre.
  • C. Lucille
    Lucille is the famous black Gibson guitar closely associated with blues legend B.B. King, who named all his guitars by this name.
  • D. Diane
    Diane is a feminine given name of Latin origin, derived from the name of the Roman goddess Diana.
  • E. Bernice
    Bernice is a feminine given name most notably borne by Bernice King, the daughter of civil rights leaders Martin Luther King Jr. and Coretta Scott King.
  • 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_69a88630519c8190a17addd83c4a3ef4 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64e22d6881909ba6ec120b320918 completed March 6, 2026, 5:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0ab743fc8190b181929109642e36 completed March 8, 2026, 11:48 p.m.
NEDg Description generation batch_69ae0b62dd048190acf6f9d76e5bfd47 completed March 8, 2026, 11:50 p.m.
NED2 Entity disambiguation (via description) batch_69ae0be695cc819093c237e19de9b731 completed March 8, 2026, 11:53 p.m.
Created at: March 4, 2026, 7:31 p.m.