Triple
T19663364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danza de los Viejitos |
E472138
|
entity |
| Predicate | usesMask |
P65729
|
FINISHED |
| Object | wooden mask |
—
|
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: wooden mask | Statement: [Danza de los Viejitos, usesMask, wooden mask]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesMask Context triple: [Danza de los Viejitos, usesMask, wooden mask]
-
A.
usesMaskIn
Indicates that an entity wears or employs a mask while present in or interacting within a specified context or location.
-
B.
usesMasking
Indicates that one entity applies or employs a masking technique or mechanism in relation to another entity or process.
-
C.
mayMask
Indicates that one entity is permitted or able to conceal, obscure, or hide another entity or its properties.
-
D.
mask
Indicates that one entity covers, conceals, or obscures another entity, typically to hide its identity, appearance, or specific features.
-
E.
typicalMaskType
chosen
Indicates the kind or category of mask that is most commonly or characteristically used or associated with an entity.
- 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_69d8e514f2e08190ba70a4449519d218 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6416671fc81908e25b0477234fa0f |
completed | April 20, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_69e514e941008190898d978d7bde91e4 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:45 p.m.