Triple
T2522830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ipanema Gisele Bündchen sandals |
E55562
|
entity |
| Predicate | footwearCategory |
P39624
|
FINISHED |
| Object | open-toe footwear |
—
|
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: open-toe footwear | Statement: [Ipanema Gisele Bündchen sandals, footwearCategory, open-toe footwear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: footwearCategory Context triple: [Ipanema Gisele Bündchen sandals, footwearCategory, open-toe footwear]
-
A.
traditionalFootwear
Indicates that the relationship involves footwear that is characteristic of, or historically associated with, a particular culture, region, or tradition.
-
B.
footType
Indicates the specific kind or classification of feet that an entity possesses or is characterized by.
-
C.
shoeLine
Indicates a relationship where a shoe is part of, or belongs to, a particular product line or collection of shoes.
-
D.
wearingClass
Indicates that one entity is wearing or dressed in an item belonging to a particular class or category of clothing or accessories.
-
E.
shoeEndorsement
Indicates a relationship where an entity publicly supports or promotes a particular shoe or shoe brand, typically as part of a sponsorship or marketing agreement.
- F. None of above. chosen
Provenance (4 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_69ab49e4749c8190813311efd1630f1b |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd23a0a548190b44393e0f823f7a9 |
completed | March 7, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69abd0c144b0819092f32a13c1d127e5 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd1487e0c8190b90dcf30586ad4cd |
completed | March 7, 2026, 7:18 a.m. |
Created at: March 6, 2026, 9:46 p.m.