Triple
T31940462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brachyteles |
E815508
|
entity |
| Predicate | vernacularNameRegion |
P40944
|
FINISHED |
| Object | muriqui in Brazil |
—
|
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: muriqui in Brazil | Statement: [Brachyteles, vernacularNameRegion, muriqui in Brazil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vernacularNameRegion Context triple: [Brachyteles, vernacularNameRegion, muriqui in Brazil]
-
A.
hasRegionalName
chosen
Indicates that an entity is known by a specific name or designation within a particular region or locality.
-
B.
regionalVariantOf
Indicates that one entity is a version or form of another that is specific to a particular geographic region or locale.
-
C.
etymologyRegion
Indicates the geographic region from which a word’s etymological origin or historical linguistic development is derived.
-
D.
vernacularNameAppliedTo
Indicates that a particular common or vernacular name is assigned or applied to an entity.
-
E.
vernacularOf
Indicates that one language or dialect is the everyday, locally used form corresponding to another, more general or standard 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_69f348f42d188190a33fc8d20ec50517 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b2713c2881909e4d5e80aed67f09 |
completed | May 3, 2026, 2:26 a.m. |
| PD | Predicate disambiguation | batch_69f6b14faf608190a25b977c0740729c |
completed | May 3, 2026, 2:22 a.m. |
Created at: May 1, 2026, 12:06 a.m.