Triple
T27571529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Disneyland Station |
E696045
|
entity |
| Predicate | hasAutomaticPlatformGates |
P4365
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Tokyo Disneyland Station, hasAutomaticPlatformGates, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAutomaticPlatformGates Context triple: [Tokyo Disneyland Station, hasAutomaticPlatformGates, yes]
-
A.
hasGatesFor
Indicates that one entity is equipped with or provides access through one or more gates intended for another entity.
-
B.
hasFaregates
Indicates that an entity is equipped with or contains faregates used to control or validate access, typically for paid entry.
-
C.
hasGate
chosen
Indicates that one entity possesses, includes, or is equipped with a gate as part of its structure or configuration.
-
D.
hasGateRange
Indicates the range of values or interval within which a gate or gating parameter is valid or operates.
-
E.
hasSouthboundPlatform
Indicates that an entity includes or is associated with a platform designated for southbound travel or service.
- 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_69f69383222c81909d8baa04129d5c81 |
completed | May 3, 2026, 12:14 a.m. |
| PD | Predicate disambiguation | batch_69f690eb1e948190aab41a89969519a5 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 27, 2026, 1:43 p.m.