Triple
T16351415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pankisi Gorge |
E397069
|
entity |
| Predicate | ethnicGroup |
P194
|
FINISHED |
| Object | Kists |
E90391
|
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: Kists | Statement: [Pankisi Gorge, ethnicGroup, Kists]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kists Context triple: [Pankisi Gorge, ethnicGroup, Kists]
-
A.
Kists
chosen
Kists are a small Nakh-speaking ethnic group living primarily in Georgia’s Pankisi Gorge, culturally and linguistically related to the Chechens of the North Caucasus.
-
B.
Kistenuten
Kistenuten is a prominent mountain peak in southwestern Norway, known as the highest point in the Ryfylke region.
-
C.
Kista
Kista is a district in northern Stockholm, Sweden, known as a major hub for information and communications technology companies and research.
-
D.
Kistelek
Kistelek is a small town in southern Hungary known for its agricultural surroundings and location within the Southern Great Plain region.
-
E.
Kesten
Kesten is a surname most notably associated with Harry Kesten, a prominent mathematician known for his work in probability theory.
- 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2facb37d0819093fe45446f1e79c1 |
completed | April 18, 2026, 3:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a003c4e6d548190b895a76a4a7268dd |
completed | May 10, 2026, 8:05 a.m. |
Created at: April 10, 2026, 5:07 a.m.