Triple
T2163751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | COP |
E46859
|
entity |
| Predicate | languageCodeContext |
P5196
|
FINISHED |
| Object | es-CO |
—
|
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: es-CO | Statement: [COP, languageCodeContext, es-CO]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageCodeContext Context triple: [COP, languageCodeContext, es-CO]
-
A.
languageCodeISO639-1
chosen
Indicates that the subject entity is associated with the specified two-letter ISO 639-1 language code.
-
B.
languageCodeISO639-2
Indicates that an entity is associated with a language identified by its ISO 639-2 three-letter code.
-
C.
languageCodeStandard
Indicates that a language code conforms to a specific standardized coding scheme (such as ISO language code standards).
-
D.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
E.
languagePair
Indicates a relationship that associates two specific languages as a paired combination, typically for translation, comparison, or mapping between them.
- 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_69a88a184cbc8190877791f6552c2484 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe8d105c819098371c35c88873dc |
completed | March 7, 2026, 5:58 a.m. |
| PD | Predicate disambiguation | batch_69abbd9c90408190b6b65498ca43ce26 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:45 p.m.