Triple
T2082258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World Discovery |
E45268
|
entity |
| Predicate | hasEntertainmentType |
P30079
|
FINISHED |
| Object | story-driven thrill rides |
—
|
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: story-driven thrill rides | Statement: [World Discovery, hasEntertainmentType, story-driven thrill rides]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEntertainmentType Context triple: [World Discovery, hasEntertainmentType, story-driven thrill rides]
-
A.
entertainmentType
chosen
Indicates the kind or category of entertainment associated with an entity or event.
-
B.
hasEntertainmentVenue
Indicates that an entity possesses, contains, or is associated with an entertainment venue as part of its facilities or offerings.
-
C.
hasHumorType
Indicates that an entity possesses or is characterized by a particular style, category, or type of humor.
-
D.
theaterType
Indicates the specific kind or category of theater associated with an entity (e.g., cinema, opera house, drama theater).
-
E.
hasNotableGenre
Indicates that an entity is significantly associated with a particular genre, such that the genre is especially characteristic or noteworthy for that 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_69a8891869c88190a02643e3bb746f59 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abba5097ac8190a723a8af2982238c |
completed | March 7, 2026, 5:40 a.m. |
| PD | Predicate disambiguation | batch_69abb7b298a48190b4bdf7c9800b058d |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:41 p.m.