Triple

T2333870
Position Surface form Disambiguated ID Type / Status
Subject Sikorsky Aircraft E44265 entity
Predicate notableProduct P1448 FINISHED
Object S-76 E93954 NE FINISHED

How this triple was built (2 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: S-76 | Statement: [Sikorsky Aircraft, notableProduct, S-76]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S-76
Context triple: [Sikorsky Aircraft, notableProduct, S-76]
  • A. Sikorsky S-76 chosen
    The Sikorsky S-76 is a medium-sized, twin-engine commercial helicopter widely used worldwide for executive transport, offshore operations, and search-and-rescue missions.
  • B. Bell 206
    The Bell 206 is a family of light, twin-blade helicopters widely used around the world for training, transport, and utility missions in both civilian and military roles.
  • C. Sikorsky S-92
    The Sikorsky S-92 is a twin-engine medium-lift helicopter widely used for offshore transport, search and rescue, and military applications.
  • D. Bell 212 helicopter
    The Bell 212 helicopter is a twin-engine, medium utility helicopter widely used for military transport, search and rescue, and general support missions around the world.
  • E. Airbus Helicopters EC135
    The Airbus Helicopters EC135 is a twin-engine light utility helicopter widely used around the world for military training, law enforcement, emergency medical services, and civilian transport.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a889132b488190bbb43ad4780ddd92 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abc66d7ea081908867ff494b70df1e completed March 7, 2026, 6:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae8979bca08190aac46ef3dc1a2be2 completed March 9, 2026, 8:48 a.m.
Created at: March 4, 2026, 7:51 p.m.