Triple
T5725722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peninsular Spanish |
E126258
|
entity |
| Predicate | typicalVocabulary |
P56045
|
FINISHED |
| Object | use of ordenador for computer |
—
|
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: use of ordenador for computer | Statement: [Peninsular Spanish, typicalVocabulary, use of ordenador for computer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalVocabulary Context triple: [Peninsular Spanish, typicalVocabulary, use of ordenador for computer]
-
A.
typicalTerm
chosen
Indicates that something is a standard, representative, or characteristic term typically associated with a given concept or context.
-
B.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
C.
languageTerm
Indicates that one entity is a linguistic expression (word, phrase, or term) used to denote or label the other entity.
-
D.
movementVocabulary
Indicates a relationship where an entity possesses or uses a characteristic set of movement patterns, gestures, or motion styles as its expressive or functional "vocabulary."
-
E.
typicalBase
Indicates that one entity serves as the standard or most representative base or foundation for another entity in typical or common cases.
- 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_69c0082f723881908ce8bb13a0c0f8b7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029014588819094a2a0f6f9b66bab |
completed | March 22, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c021c6488881909bed4a4534d57f70 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:47 p.m.