Triple
T7175727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Istanbul Metro |
E167312
|
entity |
| Predicate | connectsDistrict |
P2564
|
FINISHED |
| Object | Avcılar |
E688496
|
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: Avcılar | Statement: [Istanbul Metro, connectsDistrict, Avcılar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avcılar Context triple: [Istanbul Metro, connectsDistrict, Avcılar]
-
A.
Avcılar
chosen
Avcılar is a district on the European side of Istanbul, Turkey, known for its residential areas, university campus, and location along the Marmara Sea.
-
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.
Ataşehir
Ataşehir is a modern residential and business district on the Asian side of Istanbul, known for its high-rise developments and financial centers.
-
D.
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.
-
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_69c68889a2748190a316c5e65360361a |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e88ec6a8819083cbc3f4c39b8c79 |
completed | March 27, 2026, 8:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9162980708190be2a347b2322c09c |
completed | March 29, 2026, 12:08 p.m. |
Created at: March 27, 2026, 2:48 p.m.