Triple
T10607869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | little black dress |
E275922
|
entity |
| Predicate | hasTypicalNeckline |
P49300
|
FINISHED |
| Object | round neckline |
—
|
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: round neckline | Statement: [little black dress, hasTypicalNeckline, round neckline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalNeckline Context triple: [little black dress, hasTypicalNeckline, round neckline]
-
A.
garmentType
Indicates the specific kind or category of garment associated with an entity.
-
B.
neckCharacteristic
chosen
Indicates that an entity has a specific attribute, feature, or quality related to its neck.
-
C.
coatCharacteristic
Indicates that one entity has a particular property, feature, or quality that characterizes its outer covering or surface.
-
D.
fashionCharacteristic
Indicates a relationship where one entity possesses or exhibits a particular style, trend, or fashion-related attribute in relation to another.
-
E.
typicalFit
Indicates that one entity is a usual, expected, or characteristic match or correspondence for another in a given context.
- 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_69d6aaf948d88190806cc3a8c47a3fb2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d6df4c38c881908f69bb757b8e03f5 |
completed | April 8, 2026, 11:05 p.m. |
| PD | Predicate disambiguation | batch_69d6dd72c1288190adbb5e79e94c044a |
completed | April 8, 2026, 10:57 p.m. |
Created at: April 8, 2026, 7:32 p.m.