Triple
T24744652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nuche |
E618659
|
entity |
| Predicate | contrastsWithExonym |
P11289
|
FINISHED |
| Object | Ute |
—
|
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: Ute | Statement: [Nuche, contrastsWithExonym, Ute]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contrastsWithExonym Context triple: [Nuche, contrastsWithExonym, Ute]
-
A.
hasExonym
Indicates that one entity is known by an alternative name or designation in another language or cultural context.
-
B.
exonymStatus
Indicates the status or classification of a name used in one language to refer to a place, people, or entity known by a different name in its own language.
-
C.
nameContrastsWith
Indicates that one name is deliberately chosen or used to highlight a difference or opposition in meaning, style, or identity relative to another name.
-
D.
oftenContrastedWith
chosen
Indicates that one entity is frequently compared to another in a way that highlights their differences or opposing characteristics.
-
E.
contrastsWithMajorityLanguage
Indicates that one language or linguistic feature is notably different from, and stands in opposition to, the dominant or majority language 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_69e2fab8f95c81908bb9e552cf3280c2 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f42d9000b8819081ea2605f3c193d6 |
completed | May 1, 2026, 4:35 a.m. |
| PD | Predicate disambiguation | batch_69f420f471a0819095a6cd24ed8f7476 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 4:21 a.m.