Triple
T29959709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cold Shoulder |
E761006
|
entity |
| Predicate | typicalNeckline |
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: [Cold Shoulder, typicalNeckline, round neckline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNeckline Context triple: [Cold Shoulder, typicalNeckline, round neckline]
-
A.
typicalShoulderLine
Indicates that one entity has a shoulder line that is characteristic or standard for the type, style, or category represented by the other entity.
-
B.
typicalHemlineLength
Indicates the usual or characteristic length of the hemline associated with an item, style, or category of clothing.
-
C.
hasTypicalSleeveStyle
Indicates the usual or characteristic sleeve design associated with an item, such as a garment or uniform.
-
D.
typicalFit
Indicates that one entity is a usual, expected, or characteristic match or correspondence for another in a given context.
-
E.
neckCharacteristic
chosen
Indicates that an entity has a specific attribute, feature, or quality related to its neck.
- 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_69f22466327481908ba6db916837bece |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a031c6c728c81909c1d010048df71c3 |
completed | May 12, 2026, 12:26 p.m. |
| PD | Predicate disambiguation | batch_6a031bfc3b74819098c551096b1fcf00 |
completed | May 12, 2026, 12:24 p.m. |
Created at: April 29, 2026, 6:28 p.m.