Triple
T24552353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Awaji Ningyō Jōruri puppet theater |
E607406
|
entity |
| Predicate | puppetOperatorsPerPuppet |
P84129
|
FINISHED |
| Object | three |
—
|
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: three | Statement: [Awaji Ningyō Jōruri puppet theater, puppetOperatorsPerPuppet, three]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: puppetOperatorsPerPuppet Context triple: [Awaji Ningyō Jōruri puppet theater, puppetOperatorsPerPuppet, three]
-
A.
hasOperatorPerChannelCount
Indicates that each channel in a system or context is associated with a specific number of operators assigned to it.
-
B.
operatedAmong
Indicates that an entity carried out operations or activities within, or in coordination with, a specified group, set, or collection of other entities.
-
C.
numberOfPerformers
chosen
Indicates the quantity of performers involved in a given event, act, or performance.
-
D.
typicalOperator
Indicates that an entity commonly or normally performs operations on, or acts upon, another entity in a standard or expected manner.
-
E.
operatorCapacity
Indicates the maximum workload or volume of tasks that an operator is able to handle within a given context or time frame.
- 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_69e2c4cae1b88190825e88d5ce8aa61e |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a8cdb6b88190ad17a9b3ba607fb3 |
completed | April 30, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b99e7c8190ba7e2dc8729a314a |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:27 a.m.