Triple
T16499084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Summer of Love |
E400755
|
entity |
| Predicate | hasAssociatedFashion |
P68143
|
FINISHED |
| Object | baggy jeans |
—
|
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: baggy jeans | Statement: [Second Summer of Love, hasAssociatedFashion, baggy jeans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedFashion Context triple: [Second Summer of Love, hasAssociatedFashion, baggy jeans]
-
A.
hasGarment
Indicates that one entity possesses, wears, or is associated with a particular garment.
-
B.
fashionCharacteristic
chosen
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
C.
typicallyWornWith
Indicates that one item of clothing or accessory is commonly or customarily worn together with another.
-
D.
fashionLabel
Indicates that an entity is a fashion brand or label associated with the design, production, or marketing of clothing or accessories.
-
E.
clothingFeature
Indicates that one entity has a specific clothing-related attribute, detail, or characteristic associated with it.
- 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_69d88381f6148190819958a038be990e |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e35b96881908c9d339eea9e4314 |
completed | April 18, 2026, 7:09 a.m. |
| PD | Predicate disambiguation | batch_69e296902d6c8190884ddb612b8c5b36 |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:14 a.m.