Triple
T36621474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dinn Corporation |
E904050
|
entity |
| Predicate | typeOfRollerCoasterProduced |
P63190
|
FINISHED |
| Object | traditional wooden coaster |
—
|
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: traditional wooden coaster | Statement: [Dinn Corporation, typeOfRollerCoasterProduced, traditional wooden coaster]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfRollerCoasterProduced Context triple: [Dinn Corporation, typeOfRollerCoasterProduced, traditional wooden coaster]
-
A.
rollerCoasterType
Indicates that one entity is classified as a specific type or category of roller coaster in relation to another entity.
-
B.
coasterType
chosen
Indicates the specific category or style of a coaster that characterizes its design or function.
-
C.
rollerCoasterName
Indicates that an entity is identified by the specific name of a roller coaster.
-
D.
notableCoasterModel
Indicates that a roller coaster is an especially prominent or significant example of a particular coaster model or design.
-
E.
numberOfRollerCoasters
Indicates the quantity of roller coasters associated with a given entity.
- 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_69f76e6ae750819096911e6e2d4d12c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a031b40c6d0819096f4b9787a1f09d1 |
completed | May 12, 2026, 12:21 p.m. |
| PD | Predicate disambiguation | batch_6a03191f8ee08190b3416b044869ddfd |
completed | May 12, 2026, 12:12 p.m. |
Created at: May 3, 2026, 4:11 p.m.