Triple
T23682409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Takuya Onishi |
E585063
|
entity |
| Predicate | airlineEmployer |
P153367
|
FINISHED |
| Object | All Nippon Airways |
—
|
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: All Nippon Airways | Statement: [Takuya Onishi, airlineEmployer, All Nippon Airways]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineEmployer Context triple: [Takuya Onishi, airlineEmployer, All Nippon Airways]
-
A.
airline
Indicates that an entity operates as a commercial air transport carrier providing flight services between locations.
-
B.
airlineContext
Indicates a relationship, situation, or action that specifically occurs within or is constrained by an airline-related context (such as flights, carriers, or air travel operations).
-
C.
airlineOwnerIndustry
Indicates the industry or sector in which the owner of an airline operates.
-
D.
servesAirline
Indicates that a transportation facility or location provides service for, or is regularly used by, a specified airline.
-
E.
representsAirline
Indicates that one entity serves as the airline associated with, operating, or branding the other entity (such as a flight, route, or service).
- F. None of above. chosen
Provenance (4 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_69e24901f7c08190909fd727632e823d |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b4f93dd081909040ff117a82b87e |
completed | April 29, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f155d5265881908e43a9696b6a6d0f |
completed | April 29, 2026, 12:50 a.m. |
| PDg | Predicate description generation | batch_69f157cc43a881909ed2d8b0a09b5d73 |
completed | April 29, 2026, 12:58 a.m. |
Created at: April 17, 2026, 6:51 p.m.