Triple
T37736792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joshu’s Mu |
E940297
|
entity |
| Predicate | appearsAsCaseNumber |
P81490
|
FINISHED |
| Object | Case 1 of the Mumonkan |
—
|
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: Case 1 of the Mumonkan | Statement: [Joshu’s Mu, appearsAsCaseNumber, Case 1 of the Mumonkan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearsAsCaseNumber Context triple: [Joshu’s Mu, appearsAsCaseNumber, Case 1 of the Mumonkan]
-
A.
caseNumber
Indicates the unique identifying number assigned to a particular legal or administrative case.
-
B.
tribunalNumber
Indicates the identifying number assigned to a specific tribunal within a legal or administrative system.
-
C.
associatedCourtCase
Indicates a relationship where one entity is linked to, or involved in, a particular court case.
-
D.
courtNumber
Indicates the specific numbered court (e.g., field, room, or venue) assigned or associated with an event, case, or match.
-
E.
appearsInWorkNumber
chosen
Indicates that an entity is featured or occurs within a specific numbered work in a series or collection.
- 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_69f76edefd048190a32212c5c3919531 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fed09a12648190affcd9bacf7ca275 |
completed | May 9, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69fecf91d6f481908deb60c965c433ed |
completed | May 9, 2026, 6:09 a.m. |
Created at: May 3, 2026, 4:18 p.m.