Triple
T28272999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thunder Mesa |
E712905
|
entity |
| Predicate | hasPrimaryCoaster |
P23566
|
FINISHED |
| Object | Big Thunder Mountain Railroad |
—
|
NE NERFINISHED |
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: Big Thunder Mountain Railroad | Statement: [Thunder Mesa, hasPrimaryCoaster, Big Thunder Mountain Railroad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryCoaster Context triple: [Thunder Mesa, hasPrimaryCoaster, Big Thunder Mountain Railroad]
-
A.
COASTERIs
Indicates that one entity is a coaster or functions in the role of a coaster in relation to another entity.
-
B.
hasRollerCoaster
chosen
Indicates that one entity possesses, contains, or features a roller coaster as part of it.
-
C.
hasWaterCoaster
Indicates that an entity features or includes a water-based roller coaster attraction.
-
D.
hasPrimaryAttractionType
Indicates that an entity is characterized by a main or dominant type of attraction or appeal it offers.
-
E.
coasterType
Indicates the specific category or style of a coaster that characterizes its design or function.
- 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_69efb5216c6881908020dce4aea65381 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69feb8e856d48190aa34ad8ee8376e1c |
completed | May 9, 2026, 4:32 a.m. |
| PD | Predicate disambiguation | batch_69feb82a2b6c8190a473cc25976897be |
completed | May 9, 2026, 4:29 a.m. |
Created at: April 27, 2026, 11:18 p.m.