Triple

T5933534
Position Surface form Disambiguated ID Type / Status
Subject Vinci E131991 entity
Predicate formerName P65 FINISHED
Object GTM
GTM was a former name of Vinci, the major French concessions and construction company involved in large-scale infrastructure projects worldwide.
 E555236 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: GTM | Statement: [Vinci, formerName, GTM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: GTM
Context triple: [Vinci, formerName, GTM]
  • A. GTM
    GTM is the three-letter ISO 3166-1 alpha-3 country code assigned to Guatemala.
  • B. Google Tag Manager
    Google Tag Manager is a tag management system that lets marketers and developers easily add, update, and manage tracking and analytics tags on websites and apps without modifying the underlying code directly.
  • C. GTC
    GTC is a Polish vehicle registration code assigned to a specific county within the Pomeranian Voivodeship.
  • D. ATG
    ATG is the three-letter ISO 3166-1 alpha-3 country code assigned to Antigua and Barbuda.
  • E. GTS
    GTS is a high-performance, sport-oriented variant of the Holden Monaro produced by Holden’s performance division.
  • 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: GTM
Triple: [Vinci, formerName, GTM]
Generated description
GTM was a former name of Vinci, the major French concessions and construction company involved in large-scale infrastructure projects worldwide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: GTM
Target entity description: GTM was a former name of Vinci, the major French concessions and construction company involved in large-scale infrastructure projects worldwide.
  • A. GTM
    GTM is the three-letter ISO 3166-1 alpha-3 country code assigned to Guatemala.
  • B. Google Tag Manager
    Google Tag Manager is a tag management system that lets marketers and developers easily add, update, and manage tracking and analytics tags on websites and apps without modifying the underlying code directly.
  • C. GTC
    GTC is a Polish vehicle registration code assigned to a specific county within the Pomeranian Voivodeship.
  • D. ATG
    ATG is the three-letter ISO 3166-1 alpha-3 country code assigned to Antigua and Barbuda.
  • E. GTS
    GTS is a high-performance, sport-oriented variant of the Holden Monaro produced by Holden’s performance division.
  • 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_69c0085c55dc8190aa90e242c956e2fa completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0389f6fc881909527b928838ffcdd completed March 22, 2026, 6:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c064d2a4819096085668182cfde1 completed March 23, 2026, 4:24 a.m.
NEDg Description generation batch_69c0c109b3288190928dc4539a2872c2 completed March 23, 2026, 4:26 a.m.
NED2 Entity disambiguation (via description) batch_69c0c1f6fe60819080a00976740b6a9c completed March 23, 2026, 4:30 a.m.
Created at: March 22, 2026, 4 p.m.