Triple
T29863474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White River, Ontario |
E758385
|
entity |
| Predicate | hasMuseumOrDisplay |
P85992
|
FINISHED |
| Object | Winnie-the-Pooh historical displays |
—
|
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: Winnie-the-Pooh historical displays | Statement: [White River, Ontario, hasMuseumOrDisplay, Winnie-the-Pooh historical displays]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMuseumOrDisplay Context triple: [White River, Ontario, hasMuseumOrDisplay, Winnie-the-Pooh historical displays]
-
A.
hasMuseumComponent
Indicates that something includes, contains, or is composed of a museum or museum-related part as one of its components.
-
B.
hasMuseumFunction
Indicates that an entity serves the role or performs the function of a museum.
-
C.
hasMuseumOrTreasureHouse
chosen
Indicates that an entity contains, hosts, or is associated with a museum or treasure house.
-
D.
hasExhibits
Indicates that an entity (such as a museum, gallery, or event) displays or presents certain items, artworks, or objects as part of its collection or show.
-
E.
museumHolds
Indicates that a museum possesses, preserves, or has custody of a particular item or collection within its holdings.
- 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_69f2245b4dec8190b85f664d918a00a5 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f7cec454a88190a9f3bbee2b856636 |
completed | May 3, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f7c8977c288190997a892ec5f756ed |
completed | May 3, 2026, 10:13 p.m. |
Created at: April 29, 2026, 5:50 p.m.