Triple
T24646200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seosaengpo Port area |
E610115
|
entity |
| Predicate | hasTypicalCatch |
P138274
|
FINISHED |
| Object | shellfish |
—
|
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: shellfish | Statement: [Seosaengpo Port area, hasTypicalCatch, shellfish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalCatch Context triple: [Seosaengpo Port area, hasTypicalCatch, shellfish]
-
A.
canBeCaughtWith
Indicates that one entity is capable of being captured, obtained, or discovered using another specified entity or method.
-
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.
hasCatchFeature
Indicates that one entity possesses or is characterized by a specific catch-related feature or mechanism.
-
D.
hasTypicalSide
Indicates that one entity is the usual or characteristic side (e.g., lateral aspect) associated with another entity.
-
E.
hasTypicalCut
Indicates that one entity is characterized by or associated with a standard or typical type of cut of another 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_69e2c4d350a481909170482bc2ce6af9 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 2:33 a.m.