Triple
T7280939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beyazıt Campus |
E163143
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Fatih |
E260720
|
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: Fatih | Statement: [Beyazıt Campus, locatedIn, Fatih]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fatih Context triple: [Beyazıt Campus, locatedIn, Fatih]
-
A.
Fatih, Istanbul
chosen
Fatih is a historic central district of Istanbul known for its dense concentration of Ottoman-era architecture, religious institutions, and educational establishments.
-
B.
Nazilli
Nazilli is a town and district in Turkey’s Aydın Province, known for its agricultural production and location in the fertile Büyük Menderes River valley.
-
C.
Brusa Bezistan
Brusa Bezistan is a historic covered market building in Sarajevo’s old bazaar area, known for its Ottoman-era architecture and traditional trading stalls.
-
D.
Beştepe
Beştepe is a neighborhood in Ankara, Turkey, best known as the site of the Turkish Presidential Complex.
-
E.
Eminönü
Eminönü is a historic waterfront district in Istanbul known for its bustling ferry docks, spice and textile markets, and landmarks like the New Mosque and the Egyptian Bazaar.
- 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_69c6885c5964819085b209701769877f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb34fe0c8190a642fd3339f0cacd |
completed | March 27, 2026, 8:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7eedbbc3c81909a02c4fb63e428c0 |
completed | March 28, 2026, 3:08 p.m. |
Created at: March 27, 2026, 2:59 p.m.