Triple
T13251433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ankara 19 Mayıs Stadium |
E315540
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Altındağ, Ankara |
E330819
|
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: Altındağ, Ankara | Statement: [Ankara 19 Mayıs Stadium, locatedIn, Altındağ, Ankara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Altındağ, Ankara Context triple: [Ankara 19 Mayıs Stadium, locatedIn, Altındağ, Ankara]
-
A.
Altındağ
chosen
Altındağ is a central district of Turkey’s capital city Ankara, known for its historic quarters, cultural landmarks, and dense urban neighborhoods.
-
B.
Ataşehir
Ataşehir is a modern residential and business district on the Asian side of Istanbul, known for its high-rise developments and financial centers.
-
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.
Esenler
Esenler is a densely populated working- and middle-class district on Istanbul’s European side, known as a major transportation hub with extensive bus and metro connections.
-
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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98f73423c8190932a9edac56df383 |
completed | April 11, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a3b8ca48190863aff25f12d0e7e |
completed | May 3, 2026, 8:41 a.m. |
Created at: April 9, 2026, 9:24 p.m.