Triple
T37616691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | gomesi |
E935942
|
entity |
| Predicate | typicalWearerStatus |
P21359
|
FINISHED |
| Object | married women |
—
|
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: married women | Statement: [gomesi, typicalWearerStatus, married women]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWearerStatus Context triple: [gomesi, typicalWearerStatus, married women]
-
A.
typicalWear
Indicates that one entity is commonly or characteristically worn by the other in typical situations or contexts.
-
B.
wearerStatus
chosen
Indicates the condition or role of an entity in its capacity as a wearer of something (e.g., clothing, equipment, or an accessory).
-
C.
wearerType
Indicates the type or category of entity that is intended to wear or use the associated item.
-
D.
typicalFit
Indicates that one entity is a usual, expected, or characteristic match or correspondence for another in a given context.
-
E.
typicallyWornBy
Indicates that something (such as an item or garment) is most commonly or characteristically worn by a particular type of person or group.
- 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_69f76ed16b748190ad6add183b1be688 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a1553e08190bb7424c448cb1f33 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:18 p.m.