Triple

T29580554
Position Surface form Disambiguated ID Type / Status
Subject Lockheed-Boeing-General Dynamics team E753565 entity
Predicate competitor P1375 FINISHED
Object Northrop-McDonnell Douglas team
The Northrop–McDonnell Douglas team was an aerospace industry partnership formed to jointly compete for major U.S. military aircraft contracts.
E1874796 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: Northrop-McDonnell Douglas team | Statement: [Lockheed-Boeing-General Dynamics team, competitor, Northrop-McDonnell Douglas team]
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: Northrop-McDonnell Douglas team
Triple: [Lockheed-Boeing-General Dynamics team, competitor, Northrop-McDonnell Douglas team]
Generated description
The Northrop–McDonnell Douglas team was an aerospace industry partnership formed to jointly compete for major U.S. military aircraft contracts.

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_69f0ef80bf8c8190ad286e99f7df0c63 completed April 28, 2026, 5:33 p.m.
NER Named-entity recognition batch_69f66d78f2fc8190bc7def38615f2407 completed May 2, 2026, 9:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a262d72afbc8190906c6ab972cb6d3c completed June 8, 2026, 2:48 a.m.
NEDg Description generation batch_6a263163ffb08190b378d03e637e6e41 completed June 8, 2026, 3:05 a.m.
NED2 Entity disambiguation (via description) batch_6a26366e65a081908a92fcba16441277 completed June 8, 2026, 3:26 a.m.
Created at: April 28, 2026, 6:06 p.m.