Triple
T2256158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyoto University |
E49727
|
entity |
| Predicate | hasNotableFieldOfResearch |
P934
|
FINISHED |
| Object | physics |
—
|
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: physics | Statement: [Kyoto University, hasNotableFieldOfResearch, physics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableFieldOfResearch Context triple: [Kyoto University, hasNotableFieldOfResearch, physics]
-
A.
hasNotableResearchOutput
Indicates that an entity is associated with significant, recognized, or influential research results or publications.
-
B.
hasNotableScholar
Indicates that an entity is associated with a scholar who is recognized as particularly distinguished or influential in relation to that entity.
-
C.
hasResearchArea
chosen
Indicates that an entity (such as a person, project, or organization) is associated with or focused on a particular field or area of research.
-
D.
hasNotableFacultyField
Indicates that an institution’s notable faculty are associated with or specialize in a particular academic or professional field.
-
E.
hasResearcher
Indicates that an entity is associated with or linked to a specific researcher responsible for work, study, or investigation related to it.
- 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_69a88aaa9250819095e127d0d77e8a32 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc1570dc88190bb2b17ed4c25dbb5 |
completed | March 7, 2026, 6:10 a.m. |
| PD | Predicate disambiguation | batch_69abbdb34c148190b51e99f540f97204 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.