Triple
T33295119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tracy Chambers |
E852418
|
entity |
| Predicate | notableCostumeAspect |
P116673
|
FINISHED |
| Object | high-fashion outfits |
—
|
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: high-fashion outfits | Statement: [Tracy Chambers, notableCostumeAspect, high-fashion outfits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableCostumeAspect Context triple: [Tracy Chambers, notableCostumeAspect, high-fashion outfits]
-
A.
costumeNotability
Indicates that an entity is notable, recognized, or distinguished specifically for its costume or attire.
-
B.
costumeDesignNotability
Indicates that an entity is notable or recognized specifically for its work or achievements in costume design.
-
C.
costumeFeatures
Indicates that a costume possesses or includes specific features, attributes, or decorative elements.
-
D.
costumeDesignEmphasisOn
Indicates that a costume design places particular focus or priority on a specified element, style, feature, or thematic aspect.
-
E.
knownForCostumes
chosen
Indicates that an entity is recognized or notable specifically for its costumes, such as their design, creation, or distinctive use.
- 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_69f34966ed4c81908dc9dda82d8c7fe3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f338b881908e5593e45d764f4d |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:33 a.m.