Triple
T2993153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Middle East Technical University |
E81003
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Çankaya |
E301865
|
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: Çankaya | Statement: [Middle East Technical University, locatedIn, Çankaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Çankaya Context triple: [Middle East Technical University, locatedIn, Çankaya]
-
A.
Çankaya
chosen
Çankaya is a central district of Ankara, Turkey, known for housing key government institutions, foreign embassies, and major national landmarks.
-
B.
Sultanbeyli
Sultanbeyli is a densely populated, predominantly residential district on the Asian side of Istanbul, known for its rapid urbanization and working-class character.
-
C.
Çekmeköy
Çekmeköy is a residential district on the Asian side of Istanbul, known for its rapidly developing housing areas and proximity to forested green spaces.
-
D.
Üsküdar
Üsküdar is a historic and densely populated district of Istanbul known for its waterfront along the Bosphorus, Ottoman-era mosques, and traditional neighborhoods.
-
E.
Bayraklı
Bayraklı is a coastal district of İzmir, Turkey, known for its modern business centers, residential areas, and proximity to the city’s central urban core.
- 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_69ad8b187fc8819085914d3c9ea3142d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99e12c5c8190af7cc20e4c48bf45 |
completed | March 8, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b23592a4888190a78fcae60f4971dd |
completed | March 12, 2026, 3:40 a.m. |
Created at: March 8, 2026, 2:59 p.m.