Triple
T2216758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kristin Scott Thomas as Katherine Clifton |
E48049
|
entity |
| Predicate | costumeDesignNotability |
P36870
|
FINISHED |
| Object | periodWardrobe |
—
|
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: periodWardrobe | Statement: [Kristin Scott Thomas as Katherine Clifton, costumeDesignNotability, periodWardrobe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: costumeDesignNotability Context triple: [Kristin Scott Thomas as Katherine Clifton, costumeDesignNotability, periodWardrobe]
-
A.
costumeElement
Indicates that one item functions as a component or part of another item's costume.
-
B.
costumeType
Indicates the specific kind or category of costume associated with an entity.
-
C.
isCostumed
Indicates that an entity is wearing or otherwise adorned with a costume.
-
D.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
E.
ceremonialDressFeature
Indicates that one entity is a characteristic, component, or distinguishing element of another entity’s ceremonial dress or attire.
- F. None of above. chosen
Provenance (4 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc00f4c3881909d03301fcdfa8b67 |
completed | March 7, 2026, 6:05 a.m. |
| PD | Predicate disambiguation | batch_69abbdaa26d48190860c33fd464c4845 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbf0c2b8881908553eed5be17a9c2 |
completed | March 7, 2026, 6 a.m. |
Created at: March 4, 2026, 7:46 p.m.