Triple
T20457949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hedwig Eva Maria Kiesler |
E501844
|
entity |
| Predicate | yearOfNationalInventorsHallOfFameInduction |
P8111
|
FINISHED |
| Object | 2014 |
—
|
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: 2014 | Statement: [Hedwig Eva Maria Kiesler, yearOfNationalInventorsHallOfFameInduction, 2014]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfNationalInventorsHallOfFameInduction Context triple: [Hedwig Eva Maria Kiesler, yearOfNationalInventorsHallOfFameInduction, 2014]
-
A.
hasNumberOfInductees
Indicates the specific count of inductees associated with a given entity or context.
-
B.
yearHonored
chosen
Indicates the specific year in which an entity received an honor, award, or formal recognition.
-
C.
rockAndRollHallOfFameInductionYear
Indicates the year in which an entity was inducted into the Rock and Roll Hall of Fame.
-
D.
hasInducteesFrom
Indicates that an entity includes or contains individuals who have been formally inducted from another specified group, source, or category.
-
E.
inductedInto
Indicates that an entity has been formally admitted or entered into a group, organization, hall of fame, or similar body, typically as an honor or official recognition.
- 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_69e0b4ad4940819098cf2ff6413574e5 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e696a2a8a88190992211b09295d8ea |
completed | April 20, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69e57679eb40819086142df3e39c928e |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:33 a.m.