Triple
T475306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airbus A320 family |
E9047
|
entity |
| Predicate | competitor |
P1375
|
FINISHED |
| Object | Boeing 737 family |
E22402
|
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 737 family | Statement: [Airbus A320 family, competitor, Boeing 737 family]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boeing 737 family Context triple: [Airbus A320 family, competitor, Boeing 737 family]
-
A.
Boeing 737
chosen
The Boeing 737 is a widely used narrow-body commercial jet airliner known for being one of the best-selling passenger aircraft in aviation history.
-
B.
Airbus A320 family
The Airbus A320 family is a widely used series of narrow-body, twin-engine jet airliners designed for short- to medium-haul commercial flights.
-
C.
Boeing 777
The Boeing 777 is a long-range, wide-body twin-engine jet airliner widely used by airlines around the world for international passenger flights.
-
D.
Boeing 757
The Boeing 757 is a mid-size, narrow-body twin-engine jet airliner widely used for short- to medium- and some long-haul routes, known for its strong performance and versatility.
-
E.
Boeing 767
The Boeing 767 is a wide-body, twin-engine jet airliner widely used for medium- to long-haul commercial flights and cargo operations.
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f03b5e5081908ee3dba9d19a6871 |
completed | Feb. 28, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a46c5d827c8190b620958383d23f41 |
completed | March 1, 2026, 4:42 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.