Triple
T5592772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fiat plant, Sete Lagoas, Brazil |
E146919
|
entity |
| Predicate | languageOfWorkplace |
P18404
|
FINISHED |
| Object | Portuguese |
—
|
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: Portuguese | Statement: [Fiat plant, Sete Lagoas, Brazil, languageOfWorkplace, Portuguese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfWorkplace Context triple: [Fiat plant, Sete Lagoas, Brazil, languageOfWorkplace, Portuguese]
-
A.
languageOfExpression
Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
-
B.
languageOfWorkOrName
Indicates the language in which a work is created or a name is expressed.
-
C.
languageOfCommunications
Indicates that a specified language is used as the medium for communications associated with an entity or interaction.
-
D.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
E.
isWorkingLanguageOf
chosen
Indicates that a particular language is officially used as a medium of work, communication, or operation within a specified organization, institution, or 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_69c009036c408190981a8d690b679b67 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020bb08648190ab1f66cc3e897e6d |
completed | March 22, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69c01b16b9bc8190ab0b945507d90e05 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:38 p.m.