Triple
T30208548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masu salmon |
E768003
|
entity |
| Predicate | recreationalImportance |
P168979
|
FINISHED |
| Object | popular sport fish in East Asia |
—
|
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: popular sport fish in East Asia | Statement: [Masu salmon, recreationalImportance, popular sport fish in East Asia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recreationalImportance Context triple: [Masu salmon, recreationalImportance, popular sport fish in East Asia]
-
A.
hasRecreationalAspect
Indicates that something includes, involves, or is characterized by a recreational or leisure-related component or purpose.
-
B.
recreationUseLevel
Indicates the intensity or degree to which an entity is used for recreational activities.
-
C.
isRecreationalArea
Indicates that a place or space is designated and used primarily for leisure, relaxation, or recreational activities.
-
D.
recreationLocation
Indicates the place where a recreational activity or leisure pursuit occurs.
-
E.
recreationAccessPoint
Indicates a location or facility that serves as an entry or starting point for engaging in recreational activities.
- 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_69f2247eb0848190b4032f302d39c0d9 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f67fca43448190b108c8c1b998738f |
completed | May 2, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69f6760216108190bbb708d53a6c2c25 |
completed | May 2, 2026, 10:09 p.m. |
| PDg | Predicate description generation | batch_69f676c35f3481909b9ba18a5662d6ce |
completed | May 2, 2026, 10:12 p.m. |
Created at: April 29, 2026, 7:32 p.m.