Triple
T9206139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syukuro |
E220984
|
entity |
| Predicate | nameBearerNotableFor |
P33025
|
FINISHED |
| Object | climate modeling |
—
|
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: climate modeling | Statement: [Syukuro, nameBearerNotableFor, climate modeling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameBearerNotableFor Context triple: [Syukuro, nameBearerNotableFor, climate modeling]
-
A.
notableBearerFullName
Indicates that a full personal name is that of a notable or well-known bearer associated with the referenced entity.
-
B.
namedForNotablePersonFrom
Indicates that one entity is named in honor of a notable person who originates from another specified place or group.
-
C.
hasNamesakeNotability
Indicates that one entity is notable or recognized specifically because it shares the same name as another entity.
-
D.
holderNotableFor
chosen
Indicates that a holder (such as a person or organization) is particularly known or recognized for a specific role, achievement, work, or characteristic.
-
E.
nameBearerType
Indicates the specific role or capacity in which an entity bears or carries a given name (e.g., as a person, place, organization, or other type of name bearer).
- 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_69ca83e9d0e081908bdb71097201a06c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd947a0a08190966f22a6207c9120 |
completed | April 1, 2026, 8:37 a.m. |
| PD | Predicate disambiguation | batch_69cc660af2408190ae06eb8326e1c64e |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:26 p.m.