Triple
T2747696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azevêdo |
E60908
|
entity |
| Predicate | relatedLanguageCommunity |
P5562
|
FINISHED |
| Object | Portuguese-speaking people |
—
|
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-speaking people | Statement: [Azevêdo, relatedLanguageCommunity, Portuguese-speaking people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedLanguageCommunity Context triple: [Azevêdo, relatedLanguageCommunity, Portuguese-speaking people]
-
A.
hasLanguageCommunity
chosen
Indicates that an entity is associated with or serves a particular language community.
-
B.
sharesLanguageWith
Indicates that two entities use at least one common language for communication.
-
C.
languageDiversity
Indicates the degree to which multiple distinct languages are present and used within a given context or population.
-
D.
isCulturalLanguageOf
Indicates that a language serves as a primary medium of cultural expression, identity, and heritage for a particular group, community, or region.
-
E.
isWidelySpokenIn
Indicates that a language is spoken by a large portion of the population across many regions or communities within a specified area.
- 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_69ab4b79846081909096725374d65ce9 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb4ff7b08190b72edb6a2bc5fd19 |
completed | March 7, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69abd829f1e88190aab1d54f87c69714 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:56 p.m.