Triple
T196655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taisho era |
E3831
|
entity |
| Predicate | socialCharacter |
P662
|
FINISHED |
| Object | growth of urban middle class |
—
|
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: growth of urban middle class | Statement: [Taisho era, socialCharacter, growth of urban middle class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: socialCharacter Context triple: [Taisho era, socialCharacter, growth of urban middle class]
-
A.
characterBasedOn
Indicates that one character is modeled, inspired, or derived from another real or fictional entity.
-
B.
socialSystem
Indicates a relationship where entities are organized into a structured set of social roles, norms, and interactions that govern their collective behavior.
-
C.
characterizedBy
chosen
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
D.
notableUser
Indicates that the user holds a special or distinguished status, such as being recognized, influential, or otherwise noteworthy within a given context.
-
E.
typicalSpeaker
Indicates that the subject is a prototypical or characteristic speaker or source of utterances in the context of the object.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a2598594388190a56f36fa036eac84 |
completed | Feb. 28, 2026, 2:57 a.m. |
| PD | Predicate disambiguation | batch_69a25677da14819094cd02868fd30c83 |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.