Triple
T6854604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Awamori |
E158105
|
entity |
| Predicate | servingCustom |
P14779
|
FINISHED |
| Object | often shared from a communal bottle at the table |
—
|
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: often shared from a communal bottle at the table | Statement: [Awamori, servingCustom, often shared from a communal bottle at the table]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servingCustom Context triple: [Awamori, servingCustom, often shared from a communal bottle at the table]
-
A.
servesType
Indicates that one entity provides, offers, or is used to deliver a particular type, category, or kind of thing or service.
-
B.
servingStyle
chosen
Indicates how something (typically food or drink) is presented or offered for consumption or use.
-
C.
servesMostly
Indicates that one entity primarily functions to serve, support, or cater to another entity, more than to any other.
-
D.
servedHot
Indicates that something is provided or presented in a heated or warm state, suitable for immediate consumption.
-
E.
intendedToServe
Indicates that one entity was designed, planned, or purposed specifically to benefit, assist, or fulfill the needs 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_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.