Triple
T34525163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VOGA |
E886379
|
entity |
| Predicate | secondCharacterCountryGroup |
P199029
|
FINISHED |
| Object | O (India ICAO country designator group) |
—
|
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: O (India ICAO country designator group) | Statement: [VOGA, secondCharacterCountryGroup, O (India ICAO country designator group)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondCharacterCountryGroup Context triple: [VOGA, secondCharacterCountryGroup, O (India ICAO country designator group)]
-
A.
secondLetterCountryGroup
Indicates that the entities are grouped together based on sharing the same second letter in their country names.
-
B.
secondLetter
Indicates that one entity is the second letter (in sequence or position) of another entity, typically a string or word.
-
C.
secondBoutCountry
Indicates the country in which the second bout or match takes place.
-
D.
nationalityOfSecondVersion
Indicates that the second version of an entity has a specified national affiliation or country of origin.
-
E.
secondLargestPopulationCountry
Indicates that the subject country is the one with the second-largest population among a specified set or globally.
- 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_69f349cd7c148190aa99192b126d1527 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff1ba8694481909ceb36f26ca85612 |
completed | May 9, 2026, 11:34 a.m. |
| PD | Predicate disambiguation | batch_69ff1b27f0f08190a9e74308c5b3d1ba |
completed | May 9, 2026, 11:31 a.m. |
| PDg | Predicate description generation | batch_69ff1ba7494481908678a7a0f93dbd03 |
completed | May 9, 2026, 11:33 a.m. |
Created at: May 1, 2026, 2:02 a.m.