Triple
T29902243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BONDI |
E759439
|
entity |
| Predicate | primaryBaseCountryOfAirline |
P12358
|
FINISHED |
| Object | Argentina |
E5383
|
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: Argentina | Statement: [BONDI, primaryBaseCountryOfAirline, Argentina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryBaseCountryOfAirline Context triple: [BONDI, primaryBaseCountryOfAirline, Argentina]
-
A.
airlineBaseProvince
Indicates that a given province serves as the primary base or home region for a particular airline.
-
B.
aircraftOriginCountry
Indicates the country from which an aircraft originates, such as where it was built, registered, or primarily associated.
-
C.
airportCountryCode
Indicates the country code associated with the airport in question.
-
D.
primaryReferenceCountry
Indicates the main country that serves as the primary point of reference or association for the related entity.
-
E.
linkedAirlineCountry
chosen
Indicates that there is an association between an airline and a country, such as the country where the airline is based, registered, or primarily operates.
- F. None of above.
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_69f224600590819085e148a01c056ef6 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a01b130f6808190b86442fb16930e6e |
completed | May 11, 2026, 10:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a26f1d1cafc819081f1d1ee8fb669e5 |
completed | June 8, 2026, 4:46 p.m. |
| PD | Predicate disambiguation | batch_6a01b023157881909a802e06eced3e2f |
completed | May 11, 2026, 10:32 a.m. |
Created at: April 29, 2026, 6:07 p.m.