Triple
T2986833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ankara Metro |
E80644
|
entity |
| Predicate | servesDistrict |
P82
|
FINISHED |
| Object | Sincan |
E324364
|
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: Sincan | Statement: [Ankara Metro, servesDistrict, Sincan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sincan Context triple: [Ankara Metro, servesDistrict, Sincan]
-
A.
Sincan
chosen
Sincan is a district and rapidly growing suburban area of Turkey’s capital region, located to the west of central Ankara.
-
B.
Yenimahalle
Yenimahalle is a major district of Ankara, Turkey, known for hosting key government institutions and residential areas within the capital.
-
C.
Medinaceli
Medinaceli is a historic town in the province of Soria, Spain, known for its well-preserved medieval architecture and Roman heritage.
-
D.
Etimesgut
Etimesgut is a rapidly growing suburban district and municipality on the western side of Ankara, Turkey’s capital city.
-
E.
Çankaya
Çankaya is a central district of Ankara, Turkey, known for housing key government institutions, foreign embassies, and major national landmarks.
- 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_69ad8b16c3488190b47b6aa7a59a335b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99c88f608190bf734e0b744bf3d1 |
completed | March 8, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b224ad6c30819086a9df7fc7c51ed8 |
completed | March 12, 2026, 2:27 a.m. |
Created at: March 8, 2026, 2:59 p.m.