Triple
T33810561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cholula culture |
E866518
|
entity |
| Predicate | laterAssociatedWithLanguage |
P145372
|
FINISHED |
| Object | Nahuatl |
—
|
NE NERFINISHED |
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: Nahuatl | Statement: [Cholula culture, laterAssociatedWithLanguage, Nahuatl]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterAssociatedWithLanguage Context triple: [Cholula culture, laterAssociatedWithLanguage, Nahuatl]
-
A.
linkedToLanguage
Indicates that an entity has an association or connection with a specific language, such as being expressed in, related to, or dependent on that language.
-
B.
closelyAssociatedLanguage
Indicates that one language is closely connected to another, such as through frequent co-use, mutual influence, or strong cultural or regional association.
-
C.
hasLinguisticAffiliation
chosen
Indicates a relationship where an entity is associated with or belongs to a particular language or linguistic group.
-
D.
hasRelatedLanguage
Indicates that one language is related to another through shared linguistic origins, features, or classification.
-
E.
influencesLanguageOf
Indicates that one entity affects, shapes, or alters the language used by another entity.
- 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_69f349911a8c81908478662194b23d8c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a00037bf4148190a58593d30efdd3f8 |
completed | May 10, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_6a0000b7af608190b718fc4111bcdad8 |
completed | May 10, 2026, 3:51 a.m. |
Created at: May 1, 2026, 1:46 a.m.