Triple
T637354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chemehuevi language |
E16653
|
entity |
| Predicate | hasGrammarDescription |
P11875
|
FINISHED |
| Object | reference grammar of Chemehuevi |
—
|
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: reference grammar of Chemehuevi | Statement: [Chemehuevi language, hasGrammarDescription, reference grammar of Chemehuevi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGrammarDescription Context triple: [Chemehuevi language, hasGrammarDescription, reference grammar of Chemehuevi]
-
A.
hasDistinctGrammar
Indicates that the subject’s grammar system is different in structure or rules from that of the object.
-
B.
hasDescription
chosen
Indicates that an entity is associated with a textual description that explains or characterizes it.
-
C.
hasGrammarDifferenceFrom
Indicates that two linguistic items differ from each other in their grammatical form, structure, or rules of usage.
-
D.
hasLinguisticDescriptionBy
Indicates that something is described or characterized using language by a particular source, agent, or medium.
-
E.
grammaticalStructure
Indicates the way linguistic elements are organized and related within a sentence or phrase according to grammatical rules.
- 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_69a4936be1c88190af56540324b57da7 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ee7fdbc8190858e42bb1bfdb3ff |
completed | March 1, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69a49d0483908190a5ec42a7403c258e |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.