Triple
T31306885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chihriq fortress |
E798355
|
entity |
| Predicate | hasLanguageOfLocalRegion |
P145769
|
FINISHED |
| Object | Azerbaijani |
—
|
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: Azerbaijani | Statement: [Chihriq fortress, hasLanguageOfLocalRegion, Azerbaijani]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfLocalRegion Context triple: [Chihriq fortress, hasLanguageOfLocalRegion, Azerbaijani]
-
A.
hasLanguageInCountry
Indicates that a particular language is used or recognized within a specified country.
-
B.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
-
C.
subjectLanguageRegion
chosen
Indicates that the subject is associated with or uses a language specific to a particular geographic region.
-
D.
usesLocalLanguageVariant
Indicates that an entity employs a region-specific or localized form of a language rather than a standard or global variant.
-
E.
hasStandardLanguageNearby
Indicates that a standard or commonly used language is present in close proximity to the referenced entity.
- 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_69f224e0bd4c8190aab9b29a73f7aa3c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe12a899d4819080d48423f32eace9 |
completed | May 8, 2026, 4:43 p.m. |
| PD | Predicate disambiguation | batch_69fe0d7f6aa08190a1d2dfc025d4e0dc |
completed | May 8, 2026, 4:21 p.m. |
Created at: April 29, 2026, 9:14 p.m.