Triple
T30593599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Euskal Gramatika |
E778725
|
entity |
| Predicate | associatedLanguageAcademy |
P73454
|
FINISHED |
| Object | Euskaltzaindia |
E218535
|
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: Euskaltzaindia | Statement: [Euskal Gramatika, associatedLanguageAcademy, Euskaltzaindia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedLanguageAcademy Context triple: [Euskal Gramatika, associatedLanguageAcademy, Euskaltzaindia]
-
A.
hasLanguageAcademyOrBody
chosen
Indicates that an entity is associated with, governed by, or served by a language academy or official language-regulating body.
-
B.
languageOfTeachings
Indicates the language in which teachings, lessons, or instructional content are delivered or expressed.
-
C.
alsoUsesLanguageOfInstruction
Indicates that an entity, in addition to its primary language, uses the same language that is designated as the language of instruction in a given context.
-
D.
languageOfAwardingInstitution
Indicates the language in which the awarding institution formally grants or documents the award.
-
E.
languageOfAwardingBodies
Indicates the language or languages used by the organizations or institutions that grant the awards.
- 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_69f224a1570c8190a85d3ac330479a79 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2898c61cd48190a131b450936b7025 |
completed | June 9, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_6a0379e2fac0819089b522db3260028c |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 8:24 p.m.