Triple
T9561606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Munji |
E230686
|
entity |
| Predicate | closelyRelatedTo |
P37
|
FINISHED |
| Object | Yidgha |
E228136
|
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: Yidgha | Statement: [Munji, closelyRelatedTo, Yidgha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yidgha Context triple: [Munji, closelyRelatedTo, Yidgha]
-
A.
Yidgha
chosen
Yidgha is an Eastern Iranian language spoken primarily in parts of northern Pakistan, closely related to the Munji language and noted for its conservative phonological features.
-
B.
Gidar
Gidar is an Afroasiatic Chadic language spoken primarily in parts of northern Cameroon and neighboring regions.
-
C.
Yaghuth
Yaghuth is a pre-Islamic Arabian deity, traditionally regarded as one of the ancient gods worshipped by Arab tribes before the advent of Islam.
-
D.
Ezida
Ezida is an ancient Mesopotamian temple complex primarily dedicated to the god Nabu, associated with wisdom and writing.
-
E.
Yagon
Yagon is a coastal camping and recreation area within New South Wales’ Myall Lakes National Park, known for its beaches, dunes, and bushland setting.
- 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_69ca847e53a88190a60eed7e02257f10 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd994d31e08190b139f5ad10d8ea31 |
completed | April 1, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d152a014a48190925d52967e1fbffe |
completed | April 4, 2026, 6:04 p.m. |
Created at: March 30, 2026, 8:03 p.m.