Triple
T36191942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kin'yō Wakashū |
E1047012
|
entity |
| Predicate | compilerReputation |
P185386
|
FINISHED |
| Object | controversial innovator in waka |
—
|
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: controversial innovator in waka | Statement: [Kin'yō Wakashū, compilerReputation, controversial innovator in waka]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compilerReputation Context triple: [Kin'yō Wakashū, compilerReputation, controversial innovator in waka]
-
A.
engineeringReputation
Indicates the perceived quality, credibility, or esteem of an entity’s engineering capabilities or output as judged by others.
-
B.
securityReputation
Indicates the assessed trustworthiness or risk level associated with an entity’s security posture or behavior.
-
C.
developerReputation
Indicates the perceived trustworthiness, reliability, and quality of work associated with a developer based on their past actions or contributions.
-
D.
hasSafetyReputation
Indicates that one entity is associated with an assessment or record of safety-related reliability or trustworthiness.
-
E.
crowdReputation
Indicates the collective opinion or perceived standing of an entity as judged by a group or general audience.
- 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_69f76e3d4fbc81908c159c7beeb4ce00 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bcccd7988190aa5c931ff347d33c |
completed | May 3, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69f7be9b9ab481908328e0e8d8ac73d4 |
completed | May 3, 2026, 9:31 p.m. |
Created at: May 3, 2026, 4:08 p.m.