Triple
T4615083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rao (in Kutch) |
E100848
|
entity |
| Predicate | associatedWithLanguageCommunity |
P5562
|
FINISHED |
| Object | Kutchi speakers |
—
|
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: Kutchi speakers | Statement: [Rao (in Kutch), associatedWithLanguageCommunity, Kutchi speakers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithLanguageCommunity Context triple: [Rao (in Kutch), associatedWithLanguageCommunity, Kutchi speakers]
-
A.
hasLanguageCommunity
chosen
Indicates that an entity is associated with or serves a particular language community.
-
B.
associatedCommunity
Indicates a relationship where an entity is linked or connected to a particular community with which it is involved or identified.
-
C.
sharesLanguageWith
Indicates that two entities use at least one common language for communication.
-
D.
closelyAssociatedLanguage
Indicates that one language is closely connected to another, such as through frequent co-use, mutual influence, or strong cultural or regional association.
-
E.
languageFamilyAssociated
Indicates that there is an association or connection between a language and a particular language family.
- 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_69bd43cf363c819087fd5ab441b4a3f4 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd59c3d9ec8190a50ef03627dc351d |
completed | March 20, 2026, 2:29 p.m. |
| PD | Predicate disambiguation | batch_69bd522e2d5c8190937d0b5574f78f99 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:12 p.m.