Triple
T15819841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Papantla region of Veracruz |
E383575
|
entity |
| Predicate | currentLanguages |
P35567
|
FINISHED |
| Object | Spanish |
—
|
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: Spanish | Statement: [Papantla region of Veracruz, currentLanguages, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: currentLanguages Context triple: [Papantla region of Veracruz, currentLanguages, Spanish]
-
A.
currentNumberOfLanguages
Indicates the present count of distinct languages associated with or used by a given entity.
-
B.
hasLanguages
chosen
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
C.
extantLanguage
Indicates that a language currently exists or is in active use, as opposed to being extinct or only historically attested.
-
D.
languageVariants
Indicates that one language form is a variant or alternative version of another language.
-
E.
currentLanguageSituation
Indicates the language currently being used or in effect in a given context or situation.
- 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_69d86da2858c819090cc8481e7207b6e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0c4a6e6748190acb0791bd465587f |
completed | April 16, 2026, 11:14 a.m. |
| PD | Predicate disambiguation | batch_69e0053b847c8190945726c3ddac21cc |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:49 a.m.