Triple
T24950701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ensaios de Oscar Niemeyer e Brasília |
E624326
|
entity |
| Predicate | workTitleInPortuguese |
P157269
|
FINISHED |
| Object | Ensaios de Oscar Niemeyer e Brasília |
—
|
NE NERFINISHED |
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: Ensaios de Oscar Niemeyer e Brasília | Statement: [Ensaios de Oscar Niemeyer e Brasília, workTitleInPortuguese, Ensaios de Oscar Niemeyer e Brasília]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workTitleInPortuguese Context triple: [Ensaios de Oscar Niemeyer e Brasília, workTitleInPortuguese, Ensaios de Oscar Niemeyer e Brasília]
-
A.
workTitleInPortuguese
chosen
Indicates that the relationship specifies the title of a work as expressed in the Portuguese language.
-
B.
workTitle
Indicates the formal title or name of a work (such as a book, artwork, or composition) associated with an entity.
-
C.
workTitleType
Indicates the specific category or type of a work’s title (e.g., main title, alternative title, translated title) in relation to that work.
-
D.
workTitleWithOpus
Indicates that a work’s title is associated with a specific opus number designation.
-
E.
titleInPortuguese
Indicates that an entity has a specific title expressed in the Portuguese language.
- 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_69e2ff22e4c48190a0444b5a044f14e8 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f453035f508190be83a3d521723acf |
completed | May 1, 2026, 7:15 a.m. |
| PD | Predicate disambiguation | batch_69f44d77f6e88190a4643ab2cbef567b |
completed | May 1, 2026, 6:51 a.m. |
Created at: April 18, 2026, 5:56 a.m.