Triple
T5984981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naengmyeon |
E133204
|
entity |
| Predicate | typicallyContains |
P39152
|
FINISHED |
| Object | sliced cucumber |
—
|
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: sliced cucumber | Statement: [Naengmyeon, typicallyContains, sliced cucumber]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicallyContains Context triple: [Naengmyeon, typicallyContains, sliced cucumber]
-
A.
containsMostOf
Indicates that one entity includes the majority (but not necessarily all) of the substance, elements, or components of another entity.
-
B.
containedWith
Indicates that one entity is located or kept inside the bounds or interior space of another entity.
-
C.
typicallyHolds
chosen
Indicates that a certain relationship or condition generally holds true in typical or normal situations, though not necessarily in all cases.
-
D.
containsPortionOf
Indicates that one entity includes or holds a part, segment, or fraction of another entity.
-
E.
containsText
Indicates that one entity includes the specified text string within its content.
- 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_69c0087010d081908bb8142342d63330 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04a6dcaf08190bac27c7042e65e07 |
completed | March 22, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69c049de98648190962b14fd341c93da |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:04 p.m.