Triple
T6800220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 金本知憲 |
E156163
|
entity |
| Predicate | 打順経験 |
P73076
|
FINISHED |
| Object | クリーンナップ |
—
|
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: クリーンナップ | Statement: [金本知憲, 打順経験, クリーンナップ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 打順経験 Context triple: [金本知憲, 打順経験, クリーンナップ]
-
A.
fromNoseCame
Indicates that something originated from or was expelled out of a nose.
-
B.
Xiaoerjing
Indicates a relationship where something is written, represented, or transcribed using the Xiaoerjing (Arabic-based) script for Sinitic languages.
-
C.
gaveFirsthandExperienceOf
Indicates that one entity directly provided another entity with personal, firsthand experience of something, rather than secondhand or indirect knowledge.
-
D.
SakaeIs
Indicates that one entity is identified as or classified as "Sakae" in relation to another entity or context.
-
E.
runsAcross
Indicates that one entity moves quickly on foot from one side of another entity, area, or boundary to the opposite side, traversing it in a roughly straight path.
- 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_69c6881844448190a65822d9b39d7f88 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2e457408190a0ad9b0c48d8147c |
completed | March 27, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69c6d099bf08819089a9f9894d037e74 |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d2a8f9188190abbb8c730e7b5edf |
completed | March 27, 2026, 6:55 p.m. |
Created at: March 27, 2026, 2:15 p.m.