Triple
T38504645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsáchila |
E921730
|
entity |
| Predicate | traditionalClothingWomen |
P195542
|
FINISHED |
| Object | brightly colored skirts |
—
|
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: brightly colored skirts | Statement: [Tsáchila, traditionalClothingWomen, brightly colored skirts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalClothingWomen Context triple: [Tsáchila, traditionalClothingWomen, brightly colored skirts]
-
A.
traditionalClothingType
chosen
Indicates the type or category of traditional clothing associated with an entity.
-
B.
traditionalDressVariant
Indicates that one traditional dress is a variant or localized form of another traditional dress within the same broader cultural or stylistic tradition.
-
C.
traditionalDressMen
Indicates that the relationship involves traditional or customary clothing specifically worn by men.
-
D.
traditionalDressSimilarTo
Indicates that one traditional dress resembles or shares notable stylistic or cultural features with another traditional dress.
-
E.
traditionalDressRegion
Indicates the geographic region or area with which a particular traditional dress is associated or from which it originates.
- 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_69f76ea3c5448190aa7002fc1ba3f874 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a000efe971081909de03f875a7ad6cc |
completed | May 10, 2026, 4:52 a.m. |
| PD | Predicate disambiguation | batch_6a000c4ffe788190a5757af60aadd9f3 |
completed | May 10, 2026, 4:40 a.m. |
Created at: May 3, 2026, 4:32 p.m.