Triple

T8929674
Position Surface form Disambiguated ID Type / Status
Subject Instituto Nacional de Industria E212618 entity
Predicate subsidiary P258 FINISHED
Object Enasa
Enasa was a Spanish state-owned automotive manufacturer best known for producing Pegaso commercial vehicles and trucks.
 E766193 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: Enasa | Statement: [Instituto Nacional de Industria, subsidiary, Enasa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Enasa
Context triple: [Instituto Nacional de Industria, subsidiary, Enasa]
  • A. Citium
    Citium was an ancient city on the southern coast of Cyprus, historically significant as a Phoenician-Greek trading center and the birthplace of the Stoic philosopher Zeno.
  • B. Avisio
    Avisio is a river in northern Italy that flows through the Trentino region before joining the Adige.
  • C. Arabtec
    Arabtec is a major United Arab Emirates–based construction company known for building landmark projects, including some of the world’s tallest and most iconic skyscrapers.
  • D. Arrohateck
    Arrohateck was a Native American tribe of the Powhatan Confederacy that inhabited the region along the James River in what is now Virginia during the early colonial period.
  • E. Telesystem-Mesko
    Telesystem-Mesko is a Polish defense company known for developing advanced guided missile and precision weapon systems.
  • 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: Enasa
Triple: [Instituto Nacional de Industria, subsidiary, Enasa]
Generated description
Enasa was a Spanish state-owned automotive manufacturer best known for producing Pegaso commercial vehicles and trucks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Enasa
Target entity description: Enasa was a Spanish state-owned automotive manufacturer best known for producing Pegaso commercial vehicles and trucks.
  • A. Citium
    Citium was an ancient city on the southern coast of Cyprus, historically significant as a Phoenician-Greek trading center and the birthplace of the Stoic philosopher Zeno.
  • B. Avisio
    Avisio is a river in northern Italy that flows through the Trentino region before joining the Adige.
  • C. Arabtec
    Arabtec is a major United Arab Emirates–based construction company known for building landmark projects, including some of the world’s tallest and most iconic skyscrapers.
  • D. Arrohateck
    Arrohateck was a Native American tribe of the Powhatan Confederacy that inhabited the region along the James River in what is now Virginia during the early colonial period.
  • E. Telesystem-Mesko
    Telesystem-Mesko is a Polish defense company known for developing advanced guided missile and precision weapon systems.
  • 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_69ca8395c438819087d7cb844ab5990c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6676d5d881908ce78cbb5561a68b completed April 1, 2026, 12:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfba5e887c8190851f2fb533653c6e completed April 3, 2026, 1:02 p.m.
NEDg Description generation batch_69cfbab0b0048190a0ad002787dddffa completed April 3, 2026, 1:03 p.m.
NED2 Entity disambiguation (via description) batch_69cfbb4f1f6881908ec9e419d175d044 completed April 3, 2026, 1:06 p.m.
Created at: March 30, 2026, 6:57 p.m.