Triple
T29669986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Encruzado |
E750640
|
entity |
| Predicate | synonymInLanguage |
P3575
|
FINISHED |
| Object | Encruzado Branco |
—
|
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: Encruzado Branco | Statement: [Encruzado, synonymInLanguage, Encruzado Branco]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: synonymInLanguage Context triple: [Encruzado, synonymInLanguage, Encruzado Branco]
-
A.
equivalentEpithetLanguage
Indicates that two epithets are expressed in different languages but convey the same meaning or designation.
-
B.
languageOfWord
Indicates that a particular language is the one in which a given word is expressed or defined.
-
C.
languageEquivalent
Indicates that two linguistic expressions convey the same meaning or function across different languages or language varieties.
-
D.
hasLanguageFormOf
Indicates that one entity is a specific linguistic form, expression, or realization of the language used by another entity.
-
E.
synonym
chosen
Indicates that two terms have the same or nearly the same meaning in a given context.
- 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_69f0d62418a08190a401b127adf9f8a6 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f671c69b348190807d83fe1f81946f |
completed | May 2, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f6659f246081909821c5f452d14e8f |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 7:04 p.m.