Triple
T21175766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Esper |
E521807
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Raytheon |
—
|
NE NERFINISHED |
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: [Mark Esper, employer, Raytheon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Raytheon Context triple: [Mark Esper, employer, 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.
Raytheon Systems Limited
Raytheon Systems Limited is a UK-based defense and aerospace technology company specializing in advanced surveillance, radar, and intelligence systems.
-
C.
Northrop Grumman
Northrop Grumman is a leading American aerospace and defense technology company known for developing advanced military aircraft, spacecraft, and defense systems.
-
D.
Lockheed Martin
Lockheed Martin is a major American aerospace and defense company known for designing and producing advanced military aircraft, missiles, and space systems.
-
E.
General Dynamics
General Dynamics is a major American aerospace and defense corporation known for developing advanced military systems, including missiles, submarines, and combat vehicles.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b50e30748190b186824a206d39b9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7271597288190b04baff9ca8d866c |
completed | April 21, 2026, 7:28 a.m. |
Created at: April 16, 2026, 3 p.m.