Triple
T9971015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hakata ramen |
E196202
|
entity |
| Predicate | servingPractice |
P91367
|
FINISHED |
| Object | kaedama (noodle refill system) |
—
|
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: kaedama (noodle refill system) | Statement: [Hakata ramen, servingPractice, kaedama (noodle refill system)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servingPractice Context triple: [Hakata ramen, servingPractice, kaedama (noodle refill system)]
-
A.
servesUse
Indicates that one entity is used by or functions to serve the purpose or needs of another entity.
-
B.
servesTradition
Indicates that one entity upholds, maintains, or performs a tradition for the benefit or continuation of that tradition.
-
C.
servesOn
Indicates that one entity performs duties, functions, or holds a role as a member within another entity, such as a group, body, or organization.
-
D.
intendedToServe
Indicates that one entity was designed, planned, or purposed specifically to benefit, assist, or fulfill the needs of another entity.
-
E.
servesType
Indicates that one entity provides, offers, or is used to deliver a particular type, category, or kind of thing or service.
- F. None of above. chosen
Provenance (4 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_69ca82eea2b88190a0e511d21a31f386 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb7b96b1c8190b9d3c1171346615a |
completed | April 2, 2026, 12:26 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9daa808190b413a1b9a1e929e2 |
completed | April 1, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69cd358386f48190833c862b5b8c04b2 |
completed | April 1, 2026, 3:10 p.m. |
Created at: March 30, 2026, 8:48 p.m.