Triple
T21563601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zabaltegi |
E532102
|
entity |
| Predicate | languageOfFestivalCity |
P15031
|
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: [Zabaltegi, languageOfFestivalCity, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfFestivalCity Context triple: [Zabaltegi, languageOfFestivalCity, Spanish]
-
A.
primaryFestivalLanguage
Indicates that a particular language is the main or officially designated language used for communication and activities at a festival.
-
B.
languageOfEvent
chosen
Indicates the language in which an event is conducted, presented, or communicated.
-
C.
languageOfVenue
Indicates the language primarily used or officially designated for communication at a given venue.
-
D.
languageUsedInTourism
Indicates that a particular language is used for communication and services within tourism activities or contexts.
-
E.
hasOfficialLanguageAtVenue
Indicates that a specific language is officially designated for use at a particular venue or location.
- 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_69e0c460db088190828c64206a450273 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eed2e6c19c81909eaae408d94f0625 |
completed | April 27, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69e6320c8c2c81908bf031447d66a052 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:29 p.m.