Triple

T3042503
Position Surface form Disambiguated ID Type / Status
Subject Citroën C4 E83163 entity
Predicate automotiveClass P1776 FINISHED
Object C-segment
The C-segment is a European car size category that typically includes compact family cars positioned between smaller superminis and larger mid-size vehicles.
 E320994 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: C-segment | Statement: [Citroën C4, automotiveClass, C-segment]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: C-segment
Context triple: [Citroën C4, automotiveClass, C-segment]
  • A. C Branch
    The C Branch is a light rail service of Boston's MBTA Green Line that runs along Beacon Street between downtown Boston and the Cleveland Circle area of Brighton.
  • B. SECC
    SECC is a major exhibition and conference complex in Glasgow, Scotland, known for hosting large-scale events, concerts, and trade shows.
  • C. C-1
    C-1 is a commuter rail line in the Cercanías Madrid network that connects central Madrid with its surrounding metropolitan areas.
  • D. CSD
    CSD is the renowned Computer Science Department at Carnegie Mellon University, recognized globally for its pioneering research and education in computer science.
  • E. SCSE
    SCSE is the ICAO airport code assigned to La Florida Airport in Chile.
  • 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: C-segment
Triple: [Citroën C4, automotiveClass, C-segment]
Generated description
The C-segment is a European car size category that typically includes compact family cars positioned between smaller superminis and larger mid-size vehicles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: C-segment
Target entity description: The C-segment is a European car size category that typically includes compact family cars positioned between smaller superminis and larger mid-size vehicles.
  • A. C Branch
    The C Branch is a light rail service of Boston's MBTA Green Line that runs along Beacon Street between downtown Boston and the Cleveland Circle area of Brighton.
  • B. SECC
    SECC is a major exhibition and conference complex in Glasgow, Scotland, known for hosting large-scale events, concerts, and trade shows.
  • C. C-1
    C-1 is a commuter rail line in the Cercanías Madrid network that connects central Madrid with its surrounding metropolitan areas.
  • D. CSD
    CSD is the renowned Computer Science Department at Carnegie Mellon University, recognized globally for its pioneering research and education in computer science.
  • E. SCSE
    SCSE is the ICAO airport code assigned to La Florida Airport in Chile.
  • 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_69ad8b2298908190a7cb4e9bdbf064d0 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9b5d2a308190b4ce20efcae9b761 completed March 8, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ded35e008190be7dd72aa7537a3b completed March 11, 2026, 9:29 p.m.
NEDg Description generation batch_69b1dfa2fb28819089d7d76d9dc72e06 completed March 11, 2026, 9:33 p.m.
NED2 Entity disambiguation (via description) batch_69b1e0243a848190bce24d035a79fc0a completed March 11, 2026, 9:35 p.m.
Created at: March 8, 2026, 3:01 p.m.