Triple
T23709131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biblioteca Mário de Andrade |
E585810
|
entity |
| Predicate | alsoHoldsMaterialsInLanguage |
P32511
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Biblioteca Mário de Andrade, alsoHoldsMaterialsInLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alsoHoldsMaterialsInLanguage Context triple: [Biblioteca Mário de Andrade, alsoHoldsMaterialsInLanguage, English]
-
A.
languageOfMaterial
chosen
Indicates the language in which a given material, resource, or content is expressed or presented.
-
B.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
C.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
-
D.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
-
E.
hasLanguageEvidenceOf
Indicates that there is linguistic or textual evidence supporting, documenting, or attesting to the related entity or claim.
- 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_69e24905f77881908194d645676acd60 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b775a4288190bbee7bd4b5bbcd75 |
completed | April 29, 2026, 7:47 a.m. |
| PD | Predicate disambiguation | batch_69f155e4b1148190836ede4741dcb888 |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 6:53 p.m.