Triple
T9954793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Granary of Bolivia |
E195419
|
entity |
| Predicate | languageOfEquivalentName |
P63334
|
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: [Granary of Bolivia, languageOfEquivalentName, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfEquivalentName Context triple: [Granary of Bolivia, languageOfEquivalentName, Spanish]
-
A.
languageEquivalent
Indicates that two linguistic expressions convey the same meaning or function across different languages or language varieties.
-
B.
alternateLanguageName
chosen
Indicates that an entity has an additional name or label in a different language from its primary or default name.
-
C.
languageOfWorkOrName
Indicates the language in which a work is created or a name is expressed.
-
D.
hasEnglishName
Indicates that an entity is associated with a name expressed in the English language.
-
E.
languageCommonlyCalled
Indicates that one language is commonly referred to or known by a particular alternative name or label.
- 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_69ca82eaaa008190a54fa1a9f954b9ad |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb69631d08190ab2b1d1c22d46da7 |
completed | April 2, 2026, 12:21 a.m. |
| PD | Predicate disambiguation | batch_69cd1d97c44081908730071269f07712 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:46 p.m.