Triple
T15899000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sincan Campus |
E385534
|
entity |
| Predicate | district |
P2709
|
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: [Sincan Campus, district, Sincan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sincan Context triple: [Sincan Campus, district, 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.
Sincan district
Sincan district is a suburban area of Ankara, Turkey, known for its residential neighborhoods and industrial zones within the metropolitan region.
-
D.
Medinaceli
Medinaceli is a historic town in the province of Soria, Spain, known for its well-preserved medieval architecture and Roman heritage.
-
E.
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.
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1563bd0688190b6f7a695be0a4625 |
completed | April 16, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbc2cd84819080a90d983cd4d1a5 |
completed | May 10, 2026, 1:13 a.m. |
Created at: April 10, 2026, 4:51 a.m.