Triple
T1524619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan David Prize |
E32306
|
entity |
| Predicate | previousTargetGroup |
P10541
|
FINISHED |
| Object | established scholars |
—
|
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: established scholars | Statement: [Dan David Prize, previousTargetGroup, established scholars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousTargetGroup Context triple: [Dan David Prize, previousTargetGroup, established scholars]
-
A.
targetsGroup
chosen
Indicates that an action, influence, or effect is directed toward a specific group as its intended recipient or focus.
-
B.
previousRoute
Indicates that one route directly precedes another in an ordered sequence of routes.
-
C.
previousMode
Indicates that one mode directly precedes another in a sequence or state transition.
-
D.
secondaryTarget
Indicates that an entity serves as an additional or subordinate target in relation to a primary target within a given context or action.
-
E.
previousGround
Indicates that one entity is the immediately preceding ground or surface state relative to another in a sequence or progression.
- 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_69a885e9b0ac819093a9806ad0efc82c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93d4756888190bf3872154de11539 |
completed | March 5, 2026, 8:22 a.m. |
| PD | Predicate disambiguation | batch_69a907ac7ea081908dd95bb5cc3b9847 |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.