Triple
T7162220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gelendzhik |
E166972
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Anapa |
E137647
|
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: Anapa | Statement: [Gelendzhik, nearbyCity, Anapa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anapa Context triple: [Gelendzhik, nearbyCity, Anapa]
-
A.
Anapa
chosen
Anapa is a resort city on Russia’s Black Sea coast, known for its sandy beaches, mild climate, and popularity as a family vacation destination.
-
B.
Adra
Adra is a small settlement located within Harku Parish in northern Estonia.
-
C.
Anadia
Anadia is a municipality and town in Portugal known for its wine production and thermal spas, located in the country's Centro Region.
-
D.
Wasilla
Wasilla is a small city in south-central Alaska known as part of the Anchorage metropolitan area and for being the hometown of former governor Sarah Palin.
-
E.
Solan
Solan is a town in the Indian state of Himachal Pradesh known for its mushroom cultivation and as a growing commercial and educational hub in the region.
- 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_69c68887a5cc8190bec0ea96227164f7 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e82e4b248190ad3c3863cb93971e |
completed | March 27, 2026, 8:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7adc4b7648190969fab0351f9fd22 |
completed | March 28, 2026, 10:30 a.m. |
Created at: March 27, 2026, 2:47 p.m.