Triple
T21391749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Otoya Yamaguchi |
E527669
|
entity |
| Predicate | wroteMessageWith |
P144038
|
FINISHED |
| Object | toothbrush and toothpaste |
—
|
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: toothbrush and toothpaste | Statement: [Otoya Yamaguchi, wroteMessageWith, toothbrush and toothpaste]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wroteMessageWith Context triple: [Otoya Yamaguchi, wroteMessageWith, toothbrush and toothpaste]
-
A.
writtenTo
Indicates that something has been addressed or directed in written form to a particular recipient.
-
B.
writtenToMark
Indicates that something has been written and addressed or directed specifically to Mark.
-
C.
writtenBefore
Indicates that one written work was created or completed earlier in time than another written work.
-
D.
hasWrittenFor
Indicates that one entity has created written content (such as articles, stories, or texts) for or on behalf of another entity, typically a publication, organization, or platform.
-
E.
wroteIn
Indicates that an entity authored or composed something using a particular language, medium, or writing system.
- 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_69e0b51ff3748190935c0a513c62a12b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee62cbfef08190a33ac1f198c82cd0 |
completed | April 26, 2026, 7:09 p.m. |
| PD | Predicate disambiguation | batch_69e6162bbfc88190a3e75859941b2638 |
completed | April 20, 2026, 12:03 p.m. |
| PDg | Predicate description generation | batch_69e61b3e47f881908fb2aac9bd2bfb58 |
completed | April 20, 2026, 12:25 p.m. |
Created at: April 16, 2026, 5:13 p.m.