Triple
T172595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boeing |
E3507
|
entity |
| Predicate | majorCompetitor |
P1794
|
FINISHED |
| Object | Airbus |
E6021
|
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: Airbus | Statement: [Boeing, majorCompetitor, Airbus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Airbus Context triple: [Boeing, majorCompetitor, Airbus]
-
A.
Airbus
chosen
Airbus is a major European aerospace corporation known for designing and manufacturing commercial airliners such as the A320, A330, and A380 families.
-
B.
Boeing
Boeing is a major American aerospace company best known for designing and manufacturing commercial jetliners and military aircraft used worldwide.
-
C.
Eurofighter GmbH
Eurofighter GmbH is a multinational aerospace consortium that designs, develops, and produces the Eurofighter Typhoon multirole combat aircraft.
-
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.
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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a25bafd5808190a0a0cb2b21ce007f |
completed | Feb. 28, 2026, 3:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2fd02709c819096db4f4c242d463f |
completed | Feb. 28, 2026, 2:34 p.m. |
Created at: Feb. 28, 2026, 2:39 a.m.