Triple
T12264040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | maja (fashionable lower-class Madrilenian woman) |
E292295
|
entity |
| Predicate | typicalClothingElement |
P42160
|
FINISHED |
| Object | mantilla |
—
|
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: mantilla | Statement: [maja (fashionable lower-class Madrilenian woman), typicalClothingElement, mantilla]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalClothingElement Context triple: [maja (fashionable lower-class Madrilenian woman), typicalClothingElement, mantilla]
-
A.
garmentType
Indicates the specific kind or category of garment associated with an entity.
-
B.
coatCharacteristic
Indicates that one entity has a particular property, feature, or quality that characterizes its outer covering or surface.
-
C.
typicallyWornWith
Indicates that one item of clothing or accessory is commonly or customarily worn together with another.
-
D.
typicallyWornBy
Indicates that something (such as an item or garment) is most commonly or characteristically worn by a particular type of person or group.
-
E.
hasGarment
chosen
Indicates that one entity possesses, wears, or is associated with a particular garment.
- 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_69d6ab6856488190b5d31178d5015f8e |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9380a5e78819086bd4dfe9a83d1f5 |
completed | April 10, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69d91c4a66cc819083ce6fcaf5042af6 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.