Triple
T21458122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Türkmenbaşy |
E529394
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Krasnovodsk |
—
|
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: Krasnovodsk | Statement: [Türkmenbaşy, hasAlternativeName, Krasnovodsk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Krasnovodsk Context triple: [Türkmenbaşy, hasAlternativeName, Krasnovodsk]
-
A.
Krasnovodsk
chosen
Krasnovodsk, now known as Türkmenbaşy, is a key port city on the eastern shore of the Caspian Sea in western Turkmenistan.
-
B.
Kaspiysk
Kaspiysk is a coastal city on the Caspian Sea in the Republic of Dagestan, Russia, known for its industrial base and strategic naval facilities.
-
C.
Zheleznovodsk
Zheleznovodsk is a spa town in Russia’s Stavropol Krai, known for its mineral springs and health resorts in the Caucasus region.
-
D.
Berdyansk
Berdyansk is a port city in southeastern Ukraine on the northern coast of the Sea of Azov, known for its maritime trade, beaches, and resort facilities.
-
E.
Kirovo-Chepetsk
Kirovo-Chepetsk is an industrial city in western Russia known for its chemical and manufacturing industries and its location on the Vyatka River.
- 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_69e0c458133481908ae8b41a12c4edec |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9ec254081909a703056022f4f45 |
completed | April 23, 2026, 9:44 a.m. |
Created at: April 16, 2026, 6:08 p.m.