Triple
T20227840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenseikai |
E495437
|
entity |
| Predicate | hadMainBase |
P72117
|
FINISHED |
| Object | urban middle classes |
—
|
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: urban middle classes | Statement: [Kenseikai, hadMainBase, urban middle classes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadMainBase Context triple: [Kenseikai, hadMainBase, urban middle classes]
-
A.
hadBase
chosen
Indicates that an entity maintained or operated from a particular base location or primary site.
-
B.
hasMainEdifice
Indicates that an entity possesses or is associated with a primary or principal building or structure.
-
C.
hadFort
Indicates that an entity possessed, controlled, or contained a fort at some time.
-
D.
hadMajorFront
Indicates that an entity (such as a conflict or war) involved a significant primary front or theater of operations in a specified location or context.
-
E.
hadCustom
Indicates that an entity previously possessed or was associated with a customized or user-defined version of something.
- 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66fda9428819098467e7e8c547a07 |
completed | April 20, 2026, 6:26 p.m. |
| PD | Predicate disambiguation | batch_69e55b18609481909ab28bc8750a642f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:39 p.m.