Triple
T29211887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Budhan |
E740566
|
entity |
| Predicate | associatedWithLearning |
P107052
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Budhan, associatedWithLearning, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithLearning Context triple: [Budhan, associatedWithLearning, true]
-
A.
earntBy
Indicates that something (such as money, points, or a reward) is obtained as a result of the actions, work, or performance of a particular entity.
-
B.
associatedWithReasoning
Indicates that one entity is connected to or involved with another entity specifically through a reasoning, inference, or justification process.
-
C.
associatedWithSee
Indicates a relationship where one entity is contextually or functionally linked to another through the act or concept of seeing or visual observation.
-
D.
associatedWithSchool
Indicates a relationship where an entity has a connection or affiliation with a particular school, such as attendance, employment, or partnership.
-
E.
associatedWithSubject
chosen
Indicates a general relationship or connection between an entity and a subject, without specifying the exact nature of that association.
- 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_69f07cba2f808190a2746477d4e8345b |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_6a03232efd8481908ee25447a29ee20b |
completed | May 12, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_6a032269dcb08190907c965c28145b77 |
completed | May 12, 2026, 12:51 p.m. |
Created at: April 28, 2026, 12:11 p.m.