Triple
T19820950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angar-Burun |
E476191
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Chatyr-Dag |
—
|
NE NERFINISHED |
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: Chatyr-Dag | Statement: [Angar-Burun, locatedIn, Chatyr-Dag]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chatyr-Dag Context triple: [Angar-Burun, locatedIn, Chatyr-Dag]
-
A.
Chatyr-Dag
chosen
Chatyr-Dag is a prominent flat-topped limestone massif in the Crimean Mountains, known for its extensive karst plateaus and numerous caves.
-
B.
Sary-Tash
Sary-Tash is a remote village in southern Kyrgyzstan that serves as a key crossroads on routes linking Kyrgyzstan with China and Tajikistan through the Pamir and Alay mountain ranges.
-
C.
Chelkash
"Chelkash" is a short story by Russian writer Maksim Gorky that portrays a cynical dockside thief and explores themes of freedom, poverty, and moral ambiguity in late 19th-century Russia.
-
D.
Ust-Dzheguta
Ust-Dzheguta is a town in the Karachay-Cherkess Republic of southwestern Russia, situated in the North Caucasus region.
-
E.
Dykh-Tau
Dykh-Tau is one of the highest and most prominent mountains in the Caucasus range, located on the border of Russia and Georgia.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654fee3e48190ae728e49748ad268 |
completed | April 20, 2026, 4:31 p.m. |
Created at: April 10, 2026, 1:50 p.m.