Triple
T21837818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baščaršija Square |
E539165
|
entity |
| Predicate | hasNearbyBuilding |
P5648
|
FINISHED |
| Object | Brusa Bezistan |
—
|
NE NERFINISHED |
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: Brusa Bezistan | Statement: [Baščaršija Square, hasNearbyBuilding, Brusa Bezistan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brusa Bezistan Context triple: [Baščaršija Square, hasNearbyBuilding, Brusa Bezistan]
-
A.
Brusa Bezistan
chosen
Brusa Bezistan is a historic covered market building in Sarajevo’s old bazaar area, known for its Ottoman-era architecture and traditional trading stalls.
-
B.
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.
-
C.
Nişantaşı
Nişantaşı is an upscale neighborhood in Istanbul known for its luxury shopping streets, stylish cafes, and elegant residential buildings.
-
D.
Çankaya
Çankaya is a central district of Ankara, Turkey, known for housing key government institutions, foreign embassies, and major national landmarks.
-
E.
Beyazıt
Beyazıt is a historic district in Istanbul’s Fatih area, known for its bustling square, university campus, and proximity to major Ottoman-era landmarks and bazaars.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c475cda88190987d08f23caebdc1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0a7a9a36881909eb917f12d061ba9 |
completed | April 28, 2026, 12:27 p.m. |
Created at: April 16, 2026, 6:55 p.m.