Triple
T10224679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esra |
E243173
|
entity |
| Predicate | scriptInTurkish |
P64665
|
FINISHED |
| Object | Esra |
E243173
|
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: Esra | Statement: [Esra, scriptInTurkish, Esra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Esra Context triple: [Esra, scriptInTurkish, Esra]
-
A.
Esra
chosen
Esra is a feminine given name commonly used in Turkey and other countries with Islamic cultural influence.
-
B.
Hülya
Hülya is a feminine given name of Turkish origin commonly used in Turkey and among Turkish communities.
-
C.
Emine
Emine is a Turkish feminine given name commonly borne by women, including prominent public figures in Turkey.
-
D.
Gulnare
Gulnare is a central female character in Lord Byron’s narrative poem "The Corsair," known for her courage, passion, and pivotal role in the story’s dramatic events.
-
E.
Metehara
Metehara is a town in central Ethiopia known for its sugar plantations and proximity to both the Awash National Park and Lake Basaka.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d1f860048190bb20f7d3bf87f347 |
completed | April 7, 2026, 9:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f70a23288190a1dbb67324cfd799 |
completed | April 9, 2026, 12:47 a.m. |
Created at: April 6, 2026, 11:16 a.m.