Triple
T19484936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mehmed Reşad |
E487485
|
entity |
| Predicate | burialPlace |
P196
|
FINISHED |
| Object | Eyüp, Istanbul |
—
|
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: Eyüp, Istanbul | Statement: [Mehmed Reşad, burialPlace, Eyüp, Istanbul]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eyüp, Istanbul Context triple: [Mehmed Reşad, burialPlace, Eyüp, Istanbul]
-
A.
Eyüp, Istanbul
chosen
Eyüp, Istanbul is a historic district on the Golden Horn renowned as a major Islamic pilgrimage site and one of the city’s oldest sacred and residential areas.
-
B.
Fatih, Istanbul
Fatih is a historic central district of Istanbul known for its dense concentration of Ottoman-era architecture, religious institutions, and educational establishments.
-
C.
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.
-
D.
Fatih
Fatih is a common Turkish male given name, notably borne by the famous football manager Fatih Terim.
-
E.
Ülker
Ülker is a major Turkish food company best known for its wide range of confectionery and snack products.
- 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_69d8e8d924388190b847cb15bb3d0aff |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6343dcc748190b0df816e6ab4cafb |
completed | April 20, 2026, 2:12 p.m. |
Created at: April 10, 2026, 1:39 p.m.