Triple

T22461682
Position Surface form Disambiguated ID Type / Status
Subject Safran Seats E555243 entity
Predicate hasCompetitor P1375 FINISHED
Object Geven
Geven is an Italian manufacturer specializing in aircraft seating and interior solutions for commercial and regional airlines.
 E1538170 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: Geven | Statement: [Safran Seats, hasCompetitor, Geven]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Geven
Context triple: [Safran Seats, hasCompetitor, Geven]
  • A. Givet
    Givet is a small fortified town in northeastern France near the Belgian border, known for its strategic location along the Meuse River.
  • B. Giæver
    Giæver is a Norwegian surname borne by several notable figures in fields such as physics, literature, and public service.
  • C. Givan
    Givan is a surname most notably associated with Paul Givan, a Northern Irish politician who has served as First Minister of Northern Ireland.
  • D. Geer
    Geer is a municipality in the province of Liège in Wallonia, Belgium, known for its rural character and location in the Hesbaye region.
  • E. Geer
    Geer is a surname most notably associated with American actress and theatre director Ellen Geer and her family of performers.
  • 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: Geven
Triple: [Safran Seats, hasCompetitor, Geven]
Generated description
Geven is an Italian manufacturer specializing in aircraft seating and interior solutions for commercial and regional airlines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Geven
Target entity description: Geven is an Italian manufacturer specializing in aircraft seating and interior solutions for commercial and regional airlines.
  • A. Givet
    Givet is a small fortified town in northeastern France near the Belgian border, known for its strategic location along the Meuse River.
  • B. Giæver
    Giæver is a Norwegian surname borne by several notable figures in fields such as physics, literature, and public service.
  • C. Givan
    Givan is a surname most notably associated with Paul Givan, a Northern Irish politician who has served as First Minister of Northern Ireland.
  • D. Geer
    Geer is a municipality in the province of Liège in Wallonia, Belgium, known for its rural character and location in the Hesbaye region.
  • E. Geer
    Geer is a surname most notably associated with American actress and theatre director Ellen Geer and her family of performers.
  • 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_69e11e51fdec8190adfdf9f8a6362221 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15b7f74948190beaf6ea24ba29276 completed April 29, 2026, 1:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b0c8433348190894a06439b3461ed completed May 18, 2026, 12:56 p.m.
NEDg Description generation batch_6a0b0f24bb9c81909d2e5b08ff081ad0 completed May 18, 2026, 1:07 p.m.
NED2 Entity disambiguation (via description) batch_6a0b100675688190b493cc73e0d778fc completed May 18, 2026, 1:11 p.m.
Created at: April 16, 2026, 8:48 p.m.