Triple
T3910021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daisan Shōhōtei |
E87297
|
entity |
| Predicate | hearsCasesOfType |
P16126
|
FINISHED |
| Object | civil cases |
—
|
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: civil cases | Statement: [Daisan Shōhōtei, hearsCasesOfType, civil cases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hearsCasesOfType Context triple: [Daisan Shōhōtei, hearsCasesOfType, civil cases]
-
A.
hearsCasesUnder
chosen
Indicates that a judicial body or authority has the responsibility and power to adjudicate legal cases falling within a specified jurisdiction, category, or scope.
-
B.
hearsCasesAgainst
Indicates that one party (typically a judicial body or official) formally listens to and considers legal cases brought against another party.
-
C.
hearsCasesBetween
Indicates that a judicial body or authority formally considers and adjudicates legal disputes involving two or more parties.
-
D.
typeOfCasesHandled
Indicates the categories or kinds of cases that an entity (such as a person, organization, or system) is responsible for managing or processing.
-
E.
hasTypeOfCase
Indicates that an entity is associated with or classified under a particular type or category of case.
- 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_69aed9424514819086e9c58adde6652d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1abe2dc81909c18aeae9b286898 |
completed | March 9, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69aee75cff148190b6d5979d17fae085 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:22 p.m.