Triple
T7164418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mohiniyattam |
E167030
|
entity |
| Predicate | typicalHairstyle |
P42256
|
FINISHED |
| Object | hair bun on one side adorned with flowers |
—
|
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: hair bun on one side adorned with flowers | Statement: [Mohiniyattam, typicalHairstyle, hair bun on one side adorned with flowers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalHairstyle Context triple: [Mohiniyattam, typicalHairstyle, hair bun on one side adorned with flowers]
-
A.
hairCutOffBy
Indicates that one entity’s hair is removed or cut off by another entity.
-
B.
hairAsSymbol
Indicates that hair functions as a symbolic element representing ideas, traits, or meanings beyond its literal physical presence.
-
C.
tailpieceType
Indicates the specific kind or design of tailpiece associated with an instrument or object.
-
D.
fashionStyle
chosen
Indicates the characteristic way in which an entity dresses or presents themselves in terms of clothing and appearance.
-
E.
beardStyle
Indicates the specific style or manner in which an entity’s beard is shaped, groomed, or worn.
- 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_69c68888c10c819095e0383020225758 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e83168a08190937ff46797d94f3e |
completed | March 27, 2026, 8:27 p.m. |
| PD | Predicate disambiguation | batch_69c6e1cd5c948190a9113b23f7308c21 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:47 p.m.