Triple
T9815882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Sutter |
E238402
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Boeing |
E3507
|
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: Boeing | Statement: [Joe Sutter, employer, Boeing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boeing Context triple: [Joe Sutter, employer, Boeing]
-
A.
Boeing
chosen
Boeing is a major American aerospace company best known for designing and manufacturing commercial jetliners and military aircraft used worldwide.
-
B.
Rockwell International
Rockwell International was a major American manufacturing conglomerate best known in aerospace for building the Space Shuttle orbiters and contributing extensively to U.S. defense and space programs.
-
C.
Lockheed Aircraft Company
Lockheed Aircraft Company was a major American aerospace manufacturer known for producing influential military and civilian aircraft throughout the 20th century.
-
D.
Spirit AeroSystems
Spirit AeroSystems is one of the world’s largest non-OEM designers and manufacturers of aerostructures for commercial and defense aircraft.
-
E.
Lockheed Martin
Lockheed Martin is a major American aerospace and defense company known for designing and producing advanced military aircraft, missiles, and space systems.
- 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_69ca84dfde1481909f47c286d715f892 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb2f341648190bf8343e1124085cb |
completed | April 2, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eacbc2348190bac1cc7f41a389b9 |
completed | April 5, 2026, 4:53 a.m. |
Created at: March 30, 2026, 8:30 p.m.