Triple
T9970985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hakata ramen |
E196202
|
entity |
| Predicate | noodleTexture |
P31484
|
FINISHED |
| Object | firm |
—
|
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: firm | Statement: [Hakata ramen, noodleTexture, firm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: noodleTexture Context triple: [Hakata ramen, noodleTexture, firm]
-
A.
texture
Indicates the surface quality or feel of an entity as perceived by touch or appearance, such as being smooth, rough, soft, or coarse.
-
B.
typicalTexture
chosen
Indicates the usual or characteristic surface feel or consistency that is commonly associated with an entity.
-
C.
isPastaFilata
Indicates that something is a pasta filata cheese, i.e., a cheese made by heating and stretching the curd in hot water.
-
D.
fleshTexture
Indicates the tactile quality or surface feel of an entity’s flesh, such as how smooth, firm, soft, or coarse it is.
-
E.
plate3
Indicates that one entity is a third plate or dish associated with, supporting, or serving another entity in a given context.
- 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_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. |
Created at: March 30, 2026, 8:48 p.m.