Triple
T3571377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Worlds of Fun |
E75577
|
entity |
| Predicate | hasRollerCoaster |
P23566
|
FINISHED |
| Object |
Timber Wolf
Timber Wolf is a classic wooden roller coaster known for its intense drops and rough, fast-paced ride experience at the Worlds of Fun amusement park.
|
E368791
|
NE FINISHED |
How this triple was built (4 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: Timber Wolf | Statement: [Worlds of Fun, hasRollerCoaster, Timber Wolf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Timber Wolf Context triple: [Worlds of Fun, hasRollerCoaster, Timber Wolf]
-
A.
Wolf
Wolf is a common German surname borne by numerous notable individuals across fields such as scholarship, politics, and the arts.
-
B.
Wolf
Wolf is a song by American singer Miguel from his album "War & Leisure."
-
C.
Wolf
Wolf is a 2013 studio album by American rapper and producer Tyler, the Creator, known for its eclectic production and introspective, narrative-driven lyrics.
-
D.
Black Bear
"Black Bear" is a traditional Scottish bagpipe march widely associated with military regiments and ceremonial occasions.
-
E.
Eurasian wolves
Eurasian wolves are a widespread subspecies of the gray wolf native to much of Europe and Asia, known for their adaptability to diverse habitats and complex social pack structures.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Timber Wolf Triple: [Worlds of Fun, hasRollerCoaster, Timber Wolf]
Generated description
Timber Wolf is a classic wooden roller coaster known for its intense drops and rough, fast-paced ride experience at the Worlds of Fun amusement park.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Timber Wolf Target entity description: Timber Wolf is a classic wooden roller coaster known for its intense drops and rough, fast-paced ride experience at the Worlds of Fun amusement park.
-
A.
Wolf
Wolf is a common German surname borne by numerous notable individuals across fields such as scholarship, politics, and the arts.
-
B.
Wolf
Wolf is a song by American singer Miguel from his album "War & Leisure."
-
C.
Wolf
Wolf is a 2013 studio album by American rapper and producer Tyler, the Creator, known for its eclectic production and introspective, narrative-driven lyrics.
-
D.
Black Bear
"Black Bear" is a traditional Scottish bagpipe march widely associated with military regiments and ceremonial occasions.
-
E.
Eurasian wolves
Eurasian wolves are a widespread subspecies of the gray wolf native to much of Europe and Asia, known for their adaptability to diverse habitats and complex social pack structures.
- F. None of above. chosen
Provenance (5 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_69ad85d512708190829c8b2d3a2ccfb8 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0c32624819097a96b3d62e3d8f0 |
completed | March 8, 2026, 6:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b3bbbcf2d08190901049948df66f0c |
completed | March 13, 2026, 7:24 a.m. |
| NEDg | Description generation | batch_69b3bca07cac81908253b2b4225f3d67 |
completed | March 13, 2026, 7:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b3f5b6e66c81908700d5f3df0a864d |
completed | March 13, 2026, 11:32 a.m. |
Created at: March 8, 2026, 3:21 p.m.