Triple
T25730372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boruca people |
E645222
|
entity |
| Predicate | maskTheme |
P25955
|
FINISHED |
| Object | diablito (little devil) figures |
—
|
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: diablito (little devil) figures | Statement: [Boruca people, maskTheme, diablito (little devil) figures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maskTheme Context triple: [Boruca people, maskTheme, diablito (little devil) figures]
-
A.
maskColor
Indicates the color attribute associated with a mask.
-
B.
themeFor
chosen
Indicates that something serves as the central subject, topic, or focus for another thing (such as an event, work, or activity).
-
C.
themeChange
Indicates that an entity undergoes a change in its theme, style, or subject, typically transitioning from one thematic state or configuration to another.
-
D.
transformationTheme
Indicates a thematic relationship in which one entity centers on or explores the process, experience, or idea of transformation in another.
-
E.
mask
Indicates that one entity covers, conceals, or obscures another entity, typically to hide its identity, appearance, or specific features.
- 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_69e77e85254081908d79ee4e8715f283 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fcbb125481909d97550556700576 |
completed | May 2, 2026, 1:31 p.m. |
| PD | Predicate disambiguation | batch_69f480824a1c81908a8a492eedbc2596 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 11:12 p.m.