Triple
T195965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiffany & Co. flagship store |
E3819
|
entity |
| Predicate | mediaTypeDepictedIn |
P131
|
FINISHED |
| Object | films |
—
|
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: films | Statement: [Tiffany & Co. flagship store, mediaTypeDepictedIn, films]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediaTypeDepictedIn Context triple: [Tiffany & Co. flagship store, mediaTypeDepictedIn, films]
-
A.
mediaType
chosen
Indicates the format or category of media associated with an entity, such as text, image, audio, or video.
-
B.
artworkType
Indicates the specific category or kind of artwork that characterizes the relationship between the subject and the artwork.
-
C.
depicts
Indicates that one entity visually represents, portrays, or shows another entity.
-
D.
exhibitionType
Indicates the specific category or kind of exhibition associated with an entity (e.g., art show, trade fair, scientific exhibit).
-
E.
depictsPerson
Indicates that one entity visually represents or portrays a specific person.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a25983b49c819080f7e161904c53da |
completed | Feb. 28, 2026, 2:57 a.m. |
| PD | Predicate disambiguation | batch_69a25677da14819094cd02868fd30c83 |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.