Triple
T11068268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caucasian Tat |
E261679
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Khizi District |
E824015
|
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: Khizi District | Statement: [Caucasian Tat, region, Khizi District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Khizi District Context triple: [Caucasian Tat, region, Khizi District]
-
A.
Khizi District
chosen
Khizi District is an administrative region in northeastern Azerbaijan known for its mountainous landscapes, semi-desert areas, and proximity to the Caspian Sea.
-
B.
Qalat District
Qalat District is an administrative district in southern Afghanistan centered around the provincial capital city of Qalat.
-
C.
Farsi District
Farsi District is an administrative district located within Herat Province in western Afghanistan.
-
D.
Ziarat District
Ziarat District is a mountainous administrative region in northeastern Balochistan, Pakistan, known for its juniper forests and the historic Ziarat Residency.
-
E.
Tabasaran District
Tabasaran District is an administrative district in the Republic of Dagestan, Russia, known for its predominantly Tabasaran-speaking population and mountainous rural landscape.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aa9983c08190b0ef61603b69feac |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7992164d88190a01ed567b2529227 |
completed | April 9, 2026, 12:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4f3768c0081908d209b854dd08dd2 |
completed | April 19, 2026, 3:23 p.m. |
Created at: April 8, 2026, 9:26 p.m.