Triple
T7302271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karaköy |
E167885
|
entity |
| Predicate | connectedTo |
P37
|
FINISHED |
| Object | Eminönü |
E221497
|
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: Eminönü | Statement: [Karaköy, connectedTo, Eminönü]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eminönü Context triple: [Karaköy, connectedTo, Eminönü]
-
A.
Eminönü
chosen
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.
-
B.
Nişantaşı
Nişantaşı is an upscale neighborhood in Istanbul known for its luxury shopping streets, stylish cafes, and elegant residential buildings.
-
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.
Ortaköy
Ortaköy is a lively Bosphorus-side neighborhood in Istanbul known for its waterfront mosque, cafes, and views of the Bosporus Bridge.
-
E.
Maltepe
Maltepe is a residential and commercial district on Istanbul’s Asian side along the Sea of Marmara.
- 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_69c6888c820881909fc68f689fe1c251 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ebb09164819099c4479d48c1688a |
completed | March 27, 2026, 8:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7fa7320bc819081e0b94e8909c4aa |
completed | March 28, 2026, 3:57 p.m. |
Created at: March 27, 2026, 3:01 p.m.