Triple
T10039077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dimlî |
E205248
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Northern Zaza |
E205247
|
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: Northern Zaza | Statement: [Dimlî, hasAlternativeName, Northern Zaza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Northern Zaza Context triple: [Dimlî, hasAlternativeName, Northern Zaza]
-
A.
Zabana
Zabana is an Oceanic language spoken in the Solomon Islands, primarily on Santa Isabel Island.
-
B.
Zarda
Zarda is a landmark U.S. Supreme Court case that held federal law prohibits employment discrimination based on sexual orientation.
-
C.
Zaza
chosen
Zaza is an Iranian ethnic group primarily inhabiting eastern Turkey, known for speaking the Zazaki language and maintaining distinct cultural traditions.
-
D.
Razihi
Razihi is a highly divergent Arabic-related language spoken by a small community in the mountainous Jabal Razih region of northwestern Yemen.
-
E.
Nuzha
Nuzha is a residential district in Kuwait City known for its quiet neighborhoods and local amenities.
- 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_69ca834f70e88190b2d74828b7767ec1 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcee04afc8190904704d66e23a432 |
completed | April 2, 2026, 2:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d28268ab648190a565472d00b289c2 |
completed | April 5, 2026, 3:40 p.m. |
Created at: March 30, 2026, 8:55 p.m.