Triple
T31364408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hachiman-zukuri |
E799964
|
entity |
| Predicate | structuralArrangement |
P170589
|
FINISHED |
| Object | two buildings placed front and back |
—
|
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: two buildings placed front and back | Statement: [Hachiman-zukuri, structuralArrangement, two buildings placed front and back]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: structuralArrangement Context triple: [Hachiman-zukuri, structuralArrangement, two buildings placed front and back]
-
A.
structuralDesign
Indicates the relationship in which an entity is responsible for planning, organizing, or defining the structural configuration or framework of another entity.
-
B.
structuralAmbition
Indicates an entity’s intention or effort to change, shape, or influence an existing structure, system, or organizational framework.
-
C.
standStructure
Indicates that one entity is a vertical support or upright structural element for another entity.
-
D.
structuralCharacter
chosen
Indicates the inherent structural properties or configuration that characterize how something is built, organized, or composed.
-
E.
structureStyle
Indicates the architectural or design style characterizing how a structure is built or formed.
- 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_69f224e6b7448190ac6bf97ad7364160 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69f82ba5c8190acc54dfa7b82ee26 |
completed | May 3, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69f69d1d25e88190a7f57d323574da90 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:18 p.m.