Triple
T25101944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marcel Weber |
E628750
|
entity |
| Predicate | possibleFieldOfNotability |
P39276
|
FINISHED |
| Object | academia |
—
|
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: academia | Statement: [Marcel Weber, possibleFieldOfNotability, academia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: possibleFieldOfNotability Context triple: [Marcel Weber, possibleFieldOfNotability, academia]
-
A.
possibleCauseOfNotability
Indicates that one entity is a potential reason or contributing factor for why another entity is notable or recognized.
-
B.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
C.
notableField
chosen
Indicates the field, discipline, or area of activity for which an entity is especially known or distinguished.
-
D.
hasNamesakeNotability
Indicates that one entity is notable or recognized specifically because it shares the same name as another entity.
-
E.
hasNotableRecognitionFor
Indicates that an entity has received notable recognition, such as awards, honors, or distinctions, specifically for another entity or achievement.
- 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_69e2ff3071548190b62d1ac237397197 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f55e519978819087a1676564a74630 |
completed | May 2, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69f4a0edd10c81908a052ab864d57c54 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 18, 2026, 6:25 a.m.