Triple
T9819043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nakagin Capsule Tower |
E238479
|
entity |
| Predicate | capsuleInteriorFeatures |
P6655
|
FINISHED |
| Object | built-in bed |
—
|
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: built-in bed | Statement: [Nakagin Capsule Tower, capsuleInteriorFeatures, built-in bed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: capsuleInteriorFeatures Context triple: [Nakagin Capsule Tower, capsuleInteriorFeatures, built-in bed]
-
A.
hasInteriorFeature
chosen
Indicates that an entity contains or includes a specific feature within its interior space.
-
B.
cabinConfiguration
Indicates how the interior space of a vehicle, vessel, or aircraft is arranged and organized for occupants or cargo.
-
C.
seatFeature
Indicates that a seat possesses or is equipped with a particular feature or characteristic.
-
D.
capsuleSystem
Indicates a relationship where an entity functions as or belongs to a capsule-based system (e.g., a system organized around or implemented via capsules).
-
E.
hasCrewCompartmentMaterial
Indicates that an entity’s crew compartment is made of, or incorporates, a specified material.
- 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_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. |
Created at: March 30, 2026, 8:31 p.m.