Triple
T27571504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Disneyland Station |
E696045
|
entity |
| Predicate | servesThemePark |
P7126
|
FINISHED |
| Object | Tokyo Disneyland theme park |
—
|
NE NERFINISHED |
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: Tokyo Disneyland theme park | Statement: [Tokyo Disneyland Station, servesThemePark, Tokyo Disneyland theme park]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesThemePark Context triple: [Tokyo Disneyland Station, servesThemePark, Tokyo Disneyland theme park]
-
A.
servesAttraction
chosen
Indicates that one entity functions as or provides a service that supports or enhances the experience of a particular attraction.
-
B.
themeParkConnection
Indicates a relationship where two or more entities are connected through a theme park, such as by location, operation, partnership, or shared attractions.
-
C.
themeParkAttractionAt
Indicates that a specific theme park attraction is located at or associated with a particular theme park or site.
-
D.
themeParkPresence
Indicates that an entity is present at, located in, or associated with a theme park in the context of a given event or situation.
-
E.
themeParkAttraction
Indicates that something is an attraction or ride located within a theme park.
- 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_69ef53891af88190a193c5e2a1dac9b1 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69fcf825ca7081909d06b0df33eb33f9 |
completed | May 7, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fcf42160f0819096812a8bf590875e |
completed | May 7, 2026, 8:20 p.m. |
Created at: April 27, 2026, 1:43 p.m.