Triple

T394304
Position Surface form Disambiguated ID Type / Status
Subject Laurence K. Marshall E8946 entity
Predicate affiliation P10 FINISHED
Object Raytheon E1034 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: Raytheon | Statement: [Laurence K. Marshall, affiliation, Raytheon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Raytheon
Context triple: [Laurence K. Marshall, affiliation, Raytheon]
  • A. Raytheon Company chosen
    Raytheon Company was a major American defense contractor and industrial corporation known for developing advanced military technologies, including missile systems and radar.
  • B. Northrop Grumman
    Northrop Grumman is a leading American aerospace and defense technology company known for developing advanced military aircraft, spacecraft, and defense systems.
  • C. Lockheed Martin
    Lockheed Martin is a major American aerospace and defense company known for designing and producing advanced military aircraft, missiles, and space systems.
  • D. General Dynamics
    General Dynamics is a major American aerospace and defense corporation known for developing advanced military systems, including missiles, submarines, and combat vehicles.
  • E. BAE Systems
    BAE Systems is a major British multinational defense, security, and aerospace company that designs and manufactures advanced military aircraft, naval vessels, and other defense technologies.
  • 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_69a2e7f55c60819097aff65ea2ca2832 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec77a8a08190b6f96373aa8c1346 completed Feb. 28, 2026, 1:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4103d84bc819095f95ce4ce915114 completed March 1, 2026, 10:09 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.