Triple
T15161333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tobu Department Store Ikebukuro |
E362222
|
entity |
| Predicate | hasBakeries |
P116972
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Tobu Department Store Ikebukuro, hasBakeries, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBakeries Context triple: [Tobu Department Store Ikebukuro, hasBakeries, yes]
-
A.
hasRestaurantType
Indicates that an entity is associated with or classified as a particular type or category of restaurant.
-
B.
hasBreweryOrFacility
Indicates that an entity possesses, operates, or is associated with a brewery or brewing-related facility.
-
C.
hasRestaurant
Indicates that one entity possesses, operates, or contains a restaurant associated with it.
-
D.
hasIntegratedMicrobrewery
Indicates that an entity includes or contains a microbrewery as a built-in or internal component.
-
E.
hasCafes
Indicates that one entity possesses, contains, or includes one or more cafes within it.
- 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_69d85a087b7c81908baa94a53dac8d68 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0060f2efc8190aa0eb5fb8d4ce085 |
completed | April 15, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69deb9779acc81908ed2dad382c42dca |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec72059c08190a34f513a00185b08 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:08 a.m.