Triple
T29959706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cold Shoulder |
E761006
|
entity |
| Predicate | canIncludeDetail |
P53912
|
FINISHED |
| Object | ruffles around shoulder cut-out |
—
|
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: ruffles around shoulder cut-out | Statement: [Cold Shoulder, canIncludeDetail, ruffles around shoulder cut-out]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canIncludeDetail Context triple: [Cold Shoulder, canIncludeDetail, ruffles around shoulder cut-out]
-
A.
canIncludeNonMembersFor
Indicates that something is allowed to include or involve entities that are not members in relation to a specified target or context.
-
B.
mayIncludeMode
Indicates that one entity is allowed to contain or support a particular mode as one of its possible configurations or options.
-
C.
sometimesIncluded
Indicates that one entity is occasionally, but not always, contained within, part of, or present in association with another entity.
-
D.
mayIncludeRequirement
Indicates that something can optionally contain or encompass a particular requirement as part of its definition or structure.
-
E.
mayIncludeFeature
chosen
Indicates that one entity is allowed or able to contain, incorporate, or be associated with a particular feature.
- 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_69f6783d1944819080f26d4d2fdd1256 |
completed | May 2, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:28 p.m.