Triple
T14606874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fiambalá hot springs |
E342851
|
entity |
| Predicate | languageUsedAt |
P58450
|
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: [Fiambalá hot springs, languageUsedAt, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUsedAt Context triple: [Fiambalá hot springs, languageUsedAt, Spanish]
-
A.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
-
B.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
C.
languagesUsed
chosen
Indicates that one entity uses, employs, or is expressed in one or more languages associated with the other entity.
-
D.
languageDiscussedIn
Indicates that a particular language is the topic of discussion within a specified context, source, or discourse.
-
E.
languageCategory
Indicates the classification relationship where a language is assigned to a particular linguistic or functional category.
- 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb44d327c8190a8d20568429d0f80 |
completed | April 14, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69de656f9f4c81909f815b6629a9ee39 |
completed | April 14, 2026, 4:03 p.m. |
Created at: April 10, 2026, 1:25 a.m.