Triple
T1424650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salinas |
E30301
|
entity |
| Predicate | largeLanguageCommunity |
P5562
|
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: [Salinas, largeLanguageCommunity, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: largeLanguageCommunity Context triple: [Salinas, largeLanguageCommunity, Spanish]
-
A.
languageDiversity
Indicates the degree to which multiple distinct languages are present and used within a given context or population.
-
B.
hasLanguageCommunity
chosen
Indicates that an entity is associated with or serves a particular language community.
-
C.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
D.
mediaLanguage
Indicates the language in which a media item (such as a film, broadcast, or publication) is originally produced or presented.
-
E.
languageNeutral
Indicates that the relationship or action is independent of any specific natural language, applying uniformly across different linguistic contexts.
- 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_69a498fb823c8190a67ce4c4837e641a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c52e4ed881908d85e0cb9fe851ac |
completed | March 1, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69a4c4752abc8190a33b634c4d6fad28 |
completed | March 1, 2026, 10:57 p.m. |
Created at: March 1, 2026, 8 p.m.