Triple
T7953069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Disneyland Hotel |
E184661
|
entity |
| Predicate | themedWith |
P20708
|
FINISHED |
| Object | Disney storytelling |
—
|
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: Disney storytelling | Statement: [Shanghai Disneyland Hotel, themedWith, Disney storytelling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: themedWith Context triple: [Shanghai Disneyland Hotel, themedWith, Disney storytelling]
-
A.
themedAs
chosen
Indicates that something is characterized, styled, or organized according to a particular theme or motif.
-
B.
themeFor
Indicates that something serves as the central subject, topic, or focus for another thing (such as an event, work, or activity).
-
C.
thematicMaterial
Indicates that one entity serves as the primary recurring idea, motif, or thematic content that is developed or referenced by another entity.
-
D.
theme
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
-
E.
performedThemeFor
Indicates that an agent carried out or executed a performance specifically for a particular theme or subject.
- 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_69ca8292cba881908a64427b938dac47 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b5e51c88190abcc0534723e3660 |
completed | March 31, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69cb0473d7dc8190a25d0cf460b9fcbe |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:10 p.m.