Triple
T8358242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurricane Harbor Arlington |
E196732
|
entity |
| Predicate | typeOfWater |
P851
|
FINISHED |
| Object | freshwater attractions |
—
|
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: freshwater attractions | Statement: [Hurricane Harbor Arlington, typeOfWater, freshwater attractions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfWater Context triple: [Hurricane Harbor Arlington, typeOfWater, freshwater attractions]
-
A.
waterType
chosen
Indicates the specific kind or category of water associated with an entity (e.g., fresh, salt, brackish).
-
B.
waterbodyType
Indicates the classification of a water body according to its type (e.g., river, lake, ocean, etc.).
-
C.
typeOfWaterfall
Indicates that one entity is a specific kind or category of waterfall in relation to another entity.
-
D.
waterMassType
Indicates the classification of a body of water according to its physical or compositional type.
-
E.
waterContains
Indicates that a body or volume of water holds, includes, or has within it a specified substance, object, or 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_69ca82f08b348190bfb7881944bbff6f |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb806fa5c88190b23b6b3ee9d6ec6d |
completed | March 31, 2026, 8:06 a.m. |
| PD | Predicate disambiguation | batch_69cb70ca25548190b0f90c5384e3fb3c |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:59 p.m.