Triple
T13352615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cebeci Campus |
E318105
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Cebeci, Ankara |
E367098
|
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: Cebeci, Ankara | Statement: [Cebeci Campus, locatedIn, Cebeci, Ankara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cebeci, Ankara Context triple: [Cebeci Campus, locatedIn, Cebeci, Ankara]
-
A.
Karacabey
Karacabey is a town and district in northwestern Turkey known for its agriculture and proximity to both the Marmara Sea and the city of Bursa.
-
B.
Kalecik
Kalecik is a district and town in central Turkey known for its historic architecture and the locally famous Kalecik Karası grape variety.
-
C.
Avcılar
Avcılar is a district on the European side of Istanbul, Turkey, known for its residential areas, university campus, and location along the Marmara Sea.
-
D.
Kayseri
Kayseri is a historic city in central Turkey, known for its Seljuk and Ottoman architectural heritage and its role as a major commercial and cultural center in Anatolia.
-
E.
Keçiören
chosen
Keçiören is a densely populated metropolitan district and municipality of Ankara, known as one of the capital city’s major residential and commercial areas.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e8d520881908aa23c7102b72b72 |
completed | April 11, 2026, 1:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f49e5548190b14d09daea628e6b |
completed | May 3, 2026, 10:11 a.m. |
Created at: April 9, 2026, 9:32 p.m.