Triple
T9819021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nakagin Capsule Tower |
E238479
|
entity |
| Predicate | capsuleSize |
P90170
|
FINISHED |
| Object | approximately 10 square meters per capsule |
—
|
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: approximately 10 square meters per capsule | Statement: [Nakagin Capsule Tower, capsuleSize, approximately 10 square meters per capsule]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capsuleSize Context triple: [Nakagin Capsule Tower, capsuleSize, approximately 10 square meters per capsule]
-
A.
capsule
Indicates that one entity is a capsule containing, enclosing, or encapsulating another entity.
-
B.
capsuleName
Indicates that an entity has the specified name or label of a capsule (such as a pill, container, or encapsulated unit).
-
C.
cylinderSize
Indicates the size or capacity of a cylindrical object in the relationship.
-
D.
berrySize
Indicates the relative magnitude or dimensions of a berry in terms of its physical size.
-
E.
numberOfCapsules
Indicates the quantity or count of capsules associated with an entity or event.
- 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_69ca84dfde1481909f47c286d715f892 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb2f74e348190be8e4394ae6fe3fe |
completed | April 2, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cd03e01ea881909a7d93fc3994ace5 |
completed | April 1, 2026, 11:39 a.m. |
| PDg | Predicate description generation | batch_69cd06abc9248190a506b64e9c516d03 |
completed | April 1, 2026, 11:51 a.m. |
Created at: March 30, 2026, 8:31 p.m.