Triple
T23819257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diamond Valley Lake |
E589183
|
entity |
| Predicate | hasCatch |
P138274
|
FINISHED |
| Object | largemouth bass |
—
|
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: largemouth bass | Statement: [Diamond Valley Lake, hasCatch, largemouth bass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCatch Context triple: [Diamond Valley Lake, hasCatch, largemouth bass]
-
A.
hasCatchFeature
Indicates that one entity possesses or is characterized by a specific catch-related feature or mechanism.
-
B.
hasPrimaryCatch
chosen
Indicates that an entity (such as a fishery, vessel, or fishing activity) has a main or predominant type of catch associated with it.
-
C.
canBeCaughtWith
Indicates that one entity is capable of being captured, obtained, or discovered using another specified entity or method.
-
D.
hasException
Indicates that a general rule, process, or condition does not apply in a particular case due to a specified exception.
-
E.
catchStyle
Indicates the manner or technique with which something is caught (e.g., how an object, ball, or entity is captured or received).
- 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_69e25d18619081909c7fb89d8926f14a |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c7ad0ec88190bace5c3f00908b30 |
completed | April 29, 2026, 8:56 a.m. |
| PD | Predicate disambiguation | batch_69f156036ad48190bc2ffdaf39218bcb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:58 p.m.