Triple
T34320853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kitakata |
E880730
|
entity |
| Predicate | hasRamenStyle |
P192866
|
FINISHED |
| Object | Kitakata-style ramen |
—
|
NE NERFINISHED |
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: Kitakata-style ramen | Statement: [Kitakata, hasRamenStyle, Kitakata-style ramen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRamenStyle Context triple: [Kitakata, hasRamenStyle, Kitakata-style ramen]
-
A.
containsNoodles
Indicates that one entity (typically a dish or food item) includes noodles as one of its components.
-
B.
noodleType
Indicates the specific kind or category of noodle associated with an entity.
-
C.
hasStapleFood
Indicates that an entity’s primary or regularly consumed basic food item is another specified entity.
-
D.
hasTastingMenu
Indicates that an establishment offers a predefined multi-course tasting menu as part of its dining options.
-
E.
honkanStyle
Indicates a relationship where something follows or exhibits the characteristics of the Honkan style (a specific stylistic or design convention).
- 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_69f349b9cd508190a996a616903b3e6d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd2cf39b0c8190811b8a6fa9410560 |
completed | May 8, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69fd2ad8dd988190a9899701ba00d917 |
completed | May 8, 2026, 12:14 a.m. |
| PDg | Predicate description generation | batch_69fd2cf29f808190856ab1d43a51d5c7 |
completed | May 8, 2026, 12:23 a.m. |
Created at: May 1, 2026, 1:57 a.m.