Triple
T14812244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mülheim an der Ruhr |
E348208
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Beykoz |
E203594
|
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: Beykoz | Statement: [Mülheim an der Ruhr, hasTwinTown, Beykoz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beykoz Context triple: [Mülheim an der Ruhr, hasTwinTown, Beykoz]
-
A.
Beykoz
chosen
Beykoz is a green, waterfront district of Istanbul known for its forests, historic waterfront mansions, and scenic views along the Bosphorus.
-
B.
Sarıyer
Sarıyer is a district on the European side of Istanbul, Turkey, known for its Bosphorus coastline, historic neighborhoods, and prominent sports and educational institutions.
-
C.
Kadıköy
Kadıköy is a historic district on the Asian side of Istanbul, Turkey, known for its ancient roots (including the site of the Council of Chalcedon), vibrant cultural life, and bustling waterfront.
-
D.
Çekmeköy
Çekmeköy is a residential district on the Asian side of Istanbul, known for its rapidly developing housing areas and proximity to forested green spaces.
-
E.
Üsküdar
Üsküdar is a historic and densely populated district of Istanbul known for its waterfront along the Bosphorus, Ottoman-era mosques, and traditional neighborhoods.
- 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decf374f288190aa918b1b6b507420 |
completed | April 14, 2026, 11:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe389598848190ba15e6eea2ba2903 |
completed | May 8, 2026, 7:25 p.m. |
Created at: April 10, 2026, 1:47 a.m.