Triple
T6854602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Awamori |
E158105
|
entity |
| Predicate | agingTerminology |
P5697
|
FINISHED |
| Object | kusu refers to awamori aged 3 years or more |
—
|
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: kusu refers to awamori aged 3 years or more | Statement: [Awamori, agingTerminology, kusu refers to awamori aged 3 years or more]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: agingTerminology Context triple: [Awamori, agingTerminology, kusu refers to awamori aged 3 years or more]
-
A.
languageTerm
Indicates that one entity is a linguistic expression (word, phrase, or term) used to denote or label the other entity.
-
B.
terminologyNote
chosen
Indicates that there is an explanatory note or comment clarifying the use, meaning, or nuances of a specific term in the relationship.
-
C.
classificationTerm
Indicates that one entity serves as a categorical label or type used to classify or group another entity.
-
D.
typicalTerm
Indicates that something is a standard, representative, or characteristic term typically associated with a given concept or context.
-
E.
keyTerm
Indicates that a term functions as a primary or central concept within a given context or information structure.
- 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_69c6882fae988190864cbba788c5ebb4 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d86d5a54819088537ada9f8d1105 |
completed | March 27, 2026, 7:20 p.m. |
| PD | Predicate disambiguation | batch_69c6d0a12834819097d7e6c0b823745e |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:20 p.m.