Triple
T326032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washington Channel (adjacent area) |
E6519
|
entity |
| Predicate | recreationType |
P3451
|
FINISHED |
| Object | water-based recreation |
—
|
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-based recreation | Statement: [Washington Channel (adjacent area), recreationType, water-based recreation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recreationType Context triple: [Washington Channel (adjacent area), recreationType, water-based recreation]
-
A.
hasRecreationType
chosen
Indicates that an entity is associated with or offers a particular type or category of recreational activity.
-
B.
activityType
Indicates the specific kind or category of action or event that an entity is engaged in or associated with.
-
C.
hasRecreationActivity
Indicates that an entity provides, includes, or is associated with a particular recreational activity.
-
D.
hasRecreationFacility
Indicates that one entity provides, contains, or is equipped with a recreational facility for use by another entity or by the public.
-
E.
hasRecreationalArea
Indicates that an entity includes, provides, or is associated with a designated space intended for leisure or recreational activities.
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eb1a37c08190b1380f6bf8513a37 |
completed | Feb. 28, 2026, 1:18 p.m. |
| PD | Predicate disambiguation | batch_69a2e949364c8190bc2351f5413f5057 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.