Triple
T13605732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daikanransha Ferris Wheel |
E325055
|
entity |
| Predicate | hasGondolaType |
P11364
|
FINISHED |
| Object | standard gondola |
—
|
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: standard gondola | Statement: [Daikanransha Ferris Wheel, hasGondolaType, standard gondola]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGondolaType Context triple: [Daikanransha Ferris Wheel, hasGondolaType, standard gondola]
-
A.
gondolaType
chosen
Indicates the specific kind or category of gondola associated with an entity.
-
B.
hasVIPGondola
Indicates that something includes or is equipped with a special VIP gondola as part of its features or configuration.
-
C.
numberOfGondolas
Indicates the quantity of gondolas associated with a given entity or system.
-
D.
hasCabType
Indicates that an entity is associated with or characterized by a specific type or category of cab.
-
E.
hasCableCar
Indicates that one entity possesses, operates, or is served by a cable car system connecting it to other locations or points.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae1b3ee481909bd43ded6227a3e5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:50 p.m.