Triple
T2986625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ankara Province |
E80640
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Kazanh
Kazanh is a locality within Turkey’s Ankara Province, situated in the Central Anatolia region.
|
E454951
|
NE FINISHED |
How this triple was built (4 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: Kazanh | Statement: [Ankara Province, contains, Kazanh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kazanh Context triple: [Ankara Province, contains, Kazanh]
-
A.
Kazan
Kazan is a major city in western Russia and the capital of the Republic of Tatarstan, known for its rich Tatar-Russian cultural heritage and historic Kremlin.
-
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.
Naberezhnye Chelny
Naberezhnye Chelny is a major industrial city in Russia’s Republic of Tatarstan, best known as the home of the KamAZ truck manufacturing plant.
-
D.
Ufa
Ufa is the capital and largest city of the Republic of Bashkortostan in Russia, known as a major industrial, cultural, and economic center in the Ural region.
-
E.
Cheboksary
Cheboksary is a major city on the Volga River in western Russia and the capital of the Chuvash Republic.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kazanh Triple: [Ankara Province, contains, Kazanh]
Generated description
Kazanh is a locality within Turkey’s Ankara Province, situated in the Central Anatolia region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kazanh Target entity description: Kazanh is a locality within Turkey’s Ankara Province, situated in the Central Anatolia region.
-
A.
Kazan
Kazan is a major city in western Russia and the capital of the Republic of Tatarstan, known for its rich Tatar-Russian cultural heritage and historic Kremlin.
-
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.
Naberezhnye Chelny
Naberezhnye Chelny is a major industrial city in Russia’s Republic of Tatarstan, best known as the home of the KamAZ truck manufacturing plant.
-
D.
Ufa
Ufa is the capital and largest city of the Republic of Bashkortostan in Russia, known as a major industrial, cultural, and economic center in the Ural region.
-
E.
Cheboksary
Cheboksary is a major city on the Volga River in western Russia and the capital of the Chuvash Republic.
- F. None of above. chosen
Provenance (5 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_69ad8b16c3488190b47b6aa7a59a335b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99c76dfc8190b08bd6110ffabf25 |
completed | March 8, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bde0234b6481908dcf37da32cf856b |
completed | March 21, 2026, 12:02 a.m. |
| NEDg | Description generation | batch_69bde3aefee8819097c472928dca0869 |
completed | March 21, 2026, 12:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bde40688a0819098caec5dd544ed8d |
completed | March 21, 2026, 12:19 a.m. |
Created at: March 8, 2026, 2:59 p.m.