Triple
T23510203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zia |
E572397
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object | Ziya |
—
|
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: Ziya | Statement: [Zia, hasVariantSpelling, Ziya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ziya Context triple: [Zia, hasVariantSpelling, Ziya]
-
A.
Ziya
chosen
Ziya is a masculine given name of Turkish origin, historically associated with notable figures such as sociologist and nationalist thinker Ziya Gökalp.
-
B.
Kadir
Kadir is a masculine given name of Turkish origin commonly used in Turkey and among Turkish-speaking communities.
-
C.
Celal
Celal is a central character in Orhan Pamuk’s novel "The Black Book," around whom much of the story’s mystery and identity exploration revolves.
-
D.
Şefik
Şefik is the given name of the prominent Ottoman statesman and reformer Midhat Pasha, a key architect of the Ottoman constitution of 1876.
-
E.
Zübeyir
Zübeyir is a Turkish masculine given name, notably borne by the archaeologist and ethnographer Hamit Zübeyir Koşay.
- 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_69e245b5e4208190bac8a6509867e394 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a90455f0819092b37c69d7e73c43 |
completed | April 29, 2026, 6:45 a.m. |
Created at: April 17, 2026, 6:07 p.m.