Triple
T20903497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toru Watanabe |
E514730
|
entity |
| Predicate | settingOfExperiences |
P56736
|
FINISHED |
| Object | Tokyo student dormitory |
—
|
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: Tokyo student dormitory | Statement: [Toru Watanabe, settingOfExperiences, Tokyo student dormitory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfExperiences Context triple: [Toru Watanabe, settingOfExperiences, Tokyo student dormitory]
-
A.
settingOfExperience
chosen
Indicates that a particular context, environment, or situation serves as the backdrop or circumstances in which an experience occurs.
-
B.
experiences
Indicates that an entity undergoes, feels, or is affected by a particular event, state, or condition.
-
C.
recommendedExperience
Indicates that a certain level or type of prior experience is advised or preferred for engaging in the related activity, role, or item.
-
D.
laterExperiences
Indicates that one event, state, or experience occurs after another in time, reflecting subsequent or later experiences relative to an earlier reference point.
-
E.
experienceType
Indicates the specific kind or category of experience associated with an entity or event.
- 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_69e0b4f8a1108190bce3d31331290ced |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6e8fe4b808190bbc1bbde7a11f283 |
completed | April 21, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69e5c9ac91108190a6700fcdf2f11890 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:47 p.m.