Triple
T17156827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FARE |
E416362
|
entity |
| Predicate | usedPilotNationality |
P89422
|
FINISHED |
| Object | Spanish |
—
|
LITERAL 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: Spanish | Statement: [FARE, usedPilotNationality, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedPilotNationality Context triple: [FARE, usedPilotNationality, Spanish]
-
A.
pilotNationality
Indicates that a pilot has a specific national affiliation or citizenship.
-
B.
usedByPilotsOf
chosen
Indicates that something is utilized or operated by pilots belonging to a particular aircraft, organization, or group.
-
C.
targetNationality
Indicates that one entity has the specified nationality as its intended or designated target.
-
D.
bearerNationality
Indicates that one entity is the country or nationality associated with the bearer of another entity, such as a document or credential.
-
E.
onboardNationalities
Indicates the set of nationalities present among the people on board a given vehicle, vessel, or craft.
- F. None of above.
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_69d886d279c081909f8ff1f743ddeb69 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f40bf9ec8190b16372bcd091db9b |
completed | April 18, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69e3830d2a90819092386717dc56f0e8 |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:37 a.m.