Triple
T8861562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vedat Dalokay |
E210899
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Vedat |
E210899
|
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: Vedat | Statement: [Vedat Dalokay, givenName, Vedat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vedat Context triple: [Vedat Dalokay, givenName, Vedat]
-
A.
Vedat Dalokay
chosen
Vedat Dalokay was a prominent Turkish architect and politician best known internationally for designing Islamabad’s iconic Faisal Mosque.
-
B.
Hasan Arat
Hasan Arat is a Turkish businessman and sports executive best known for leading the Istanbul-based football club Beşiktaş JK as its chairman.
-
C.
Ahmet
Ahmet is a common male given name of Arabic origin, widely used in Turkey and other Muslim-majority countries as a variant of Ahmed.
-
D.
Kadir
Kadir is a masculine given name of Turkish origin commonly used in Turkey and among Turkish-speaking communities.
-
E.
Güntekin
Güntekin is the surname of the renowned Turkish novelist and playwright Reşat Nuri, best known for works such as "Çalıkuşu."
- 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_69ca838bbddc8190ab546d737e5d350f |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60e860888190a8a8702377db949e |
completed | April 1, 2026, 12:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfab8fef348190a25e978085e8e656 |
completed | April 3, 2026, 11:59 a.m. |
Created at: March 30, 2026, 6:50 p.m.