Triple
T34012396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mundu |
E872148
|
entity |
| Predicate | waistFasteningMethod |
P14609
|
FINISHED |
| Object | tucking the upper edge into waistband |
—
|
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: tucking the upper edge into waistband | Statement: [Mundu, waistFasteningMethod, tucking the upper edge into waistband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waistFasteningMethod Context triple: [Mundu, waistFasteningMethod, tucking the upper edge into waistband]
-
A.
beltPosition
Indicates the relative placement or alignment of a belt with respect to another object or reference point.
-
B.
beltType
Indicates the specific kind or category of belt associated with an entity.
-
C.
wearingMethod
chosen
Indicates the manner or method by which something is worn or put on.
-
D.
waistlinePosition
Indicates the relative vertical placement of a garment’s waistline on the body (e.g., high, natural, or low).
-
E.
bandType
Indicates the specific kind or category of band that an entity belongs to or is associated with.
- 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_69f349a08848819084b348d64c1879c3 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70b966860819089cf92927f47c5f1 |
completed | May 3, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69f70abe43e08190b2a30930d96247c1 |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 1:51 a.m.