Triple
T38018113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taishō Shinshū Daizōkyō |
E948549
|
entity |
| Predicate | numberOfSupplementVolumes |
P207557
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Taishō Shinshū Daizōkyō, numberOfSupplementVolumes, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSupplementVolumes Context triple: [Taishō Shinshū Daizōkyō, numberOfSupplementVolumes, 12]
-
A.
numberOfVolumes
Indicates the total count of separate volumes or parts that make up a multi-volume work or collection.
-
B.
hasThreeVolumeStructureRole
Indicates that an entity participates in or fulfills a role within a three-volume structural organization or framework.
-
C.
numberOfAdditionalChannels
Indicates the quantity of extra channels added beyond a base or default set in a given context.
-
D.
numberOfPrimaryMirrorSegments
Indicates the total count of individual segments that make up a system’s primary mirror.
-
E.
hasAuxiliaryNumberOf
Indicates that an entity is associated with an additional or secondary numerical value beyond its primary number.
- F. None of above. chosen
Provenance (4 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_69f76efc10448190aff5fb566b98f952 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037df1223c8190a5d61e4f8e6fd613 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a037a1ad6c48190bfe35d350c1b4751 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037df009f4819082e04683e6e8a106 |
completed | May 12, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:20 p.m.