Triple
T10651993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nobel lectures |
E250991
|
entity |
| Predicate | typicallyOccur |
P56761
|
FINISHED |
| Object | around Nobel Prize award date |
—
|
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: around Nobel Prize award date | Statement: [Nobel lectures, typicallyOccur, around Nobel Prize award date]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicallyOccur Context triple: [Nobel lectures, typicallyOccur, around Nobel Prize award date]
-
A.
frequentOccasion
Indicates that a particular event, situation, or condition occurs repeatedly or commonly over time.
-
B.
typicallySpared
Indicates that an entity is usually not affected by, excluded from, or left untouched by a particular action, process, or condition.
-
C.
typicalCircumstance
chosen
Indicates the usual or commonly occurring situation, condition, or context in which an event, action, or relationship typically takes place.
-
D.
typicallyObserves
Indicates that one entity, in the normal or usual course of events, observes, watches, or monitors another entity.
-
E.
occurrence
Indicates that an event, state, or condition takes place or happens at a particular time or in a particular context.
- 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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dff78ec88190a4d1863fe87245f6 |
completed | April 8, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69d6dd8753108190b799ffa0c760526e |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 9:06 p.m.