Triple
T4019988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norbert Wiener Prize in Applied Mathematics |
E91255
|
entity |
| Predicate | languageOfAwardingBodies |
P53482
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Norbert Wiener Prize in Applied Mathematics, languageOfAwardingBodies, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfAwardingBodies Context triple: [Norbert Wiener Prize in Applied Mathematics, languageOfAwardingBodies, English]
-
A.
hasAwardingBodyType
Indicates that an entity has an associated type or category describing the kind of organization or body that grants an award.
-
B.
locationOfAwardingBody
Indicates the place or venue where the awarding body confers or grants an award.
-
C.
awardingBodyField
Indicates the organization or authority that grants or confers a particular award, qualification, or certification in the described relationship.
-
D.
languageOfTeachings
Indicates the language in which teachings, lessons, or instructional content are delivered or expressed.
-
E.
accreditingBody
Indicates that an entity serves as the official organization that grants accreditation or formal recognition to another entity.
- 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_69aed9618b04819081750d979d2af098 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaab39d4819080e37cd175c89542 |
completed | March 9, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69aef8fc78ec819092d4dab88d85a141 |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefa815f2c8190818c9ffd9d1bf478 |
completed | March 9, 2026, 4:51 p.m. |
Created at: March 9, 2026, 3:35 p.m.