Triple
T5420698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One Fish, Two Fish, Red Fish, Blue Fish |
E121240
|
entity |
| Predicate | rideFeature |
P63555
|
FINISHED |
| Object | water effects |
—
|
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: water effects | Statement: [One Fish, Two Fish, Red Fish, Blue Fish, rideFeature, water effects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rideFeature Context triple: [One Fish, Two Fish, Red Fish, Blue Fish, rideFeature, water effects]
-
A.
rideSystem
Indicates that one entity uses or travels on a transportation system or service provided by another entity.
-
B.
hasRideSystem
Indicates that one entity (typically an attraction or ride) uses or is associated with a particular ride system or ride mechanism.
-
C.
hasCableCar
Indicates that one entity possesses, operates, or is served by a cable car system connecting it to other locations or points.
-
D.
ridingSpecialty
Indicates that one entity has a particular area of expertise or focus related to riding (e.g., a specific riding style, discipline, or type).
-
E.
rides
Indicates that one entity travels on or is carried by another entity as a passenger or operator.
- F. None of above. chosen
Provenance (4 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_69bd463b58d88190b258261573de9e91 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd87eac41481908a4982db5d119edd |
completed | March 20, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69bd8469f5e48190bbe5c8bdfe8925ea |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd8741e8588190863fd5cfb559136d |
completed | March 20, 2026, 5:43 p.m. |
Created at: March 20, 2026, 2:06 p.m.