Triple
T1137192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malwai dialect |
E23166
|
entity |
| Predicate | neighboringDialect |
P18451
|
FINISHED |
| Object | Majhi dialect |
—
|
LITERAL 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: Majhi dialect | Statement: [Malwai dialect, neighboringDialect, Majhi dialect]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: neighboringDialect Context triple: [Malwai dialect, neighboringDialect, Majhi dialect]
-
A.
regionalDialect
Indicates that one entity uses or is associated with a dialect specific to a particular geographic region in relation to another entity.
-
B.
hasDialectContinuumWith
chosen
Indicates that two languages or dialects are part of a continuous chain of mutually intelligible varieties, without a clear boundary separating them.
-
C.
hasNeighboringLanguages
Indicates that two languages are geographically or regionally adjacent to each other in their areas of use.
-
D.
neighboringRegion
Indicates that two regions share a common boundary or are directly adjacent to each other geographically.
-
E.
neighboringPeoples
Indicates that two peoples or ethnic groups live in adjacent or nearby territories, sharing a common border or close geographic proximity.
- F. None of above.
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_69a493ec75988190b63a11bafaec29b4 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bde18d208190848c189b2b8d585f |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4b52d48190bec2e7ad1cc8efc0 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.