Triple
T13941516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mama Klump |
E335265
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Anna Klump |
E444806
|
NE 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: Anna Klump | Statement: [Mama Klump, fullName, Anna Klump]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anna Klump Context triple: [Mama Klump, fullName, Anna Klump]
-
A.
Anna Klump
chosen
Anna Klump is a fictional character from the "Nutty Professor" comedy films, known as a member of the Klump family.
-
B.
Barbara Blomberg
Barbara Blomberg was a 16th-century German woman best known as the mistress of Holy Roman Emperor Charles V and the mother of his illegitimate son, John of Austria (the Elder).
-
C.
Cornelia Srebnick
Cornelia Srebnick is a central character in the film "While We're Young," portrayed as a woman navigating marriage, creativity, and generational tensions in contemporary New York City.
-
D.
Ann Fischer
Ann Fischer was the wife of prominent American television newscaster David Brinkley.
-
E.
Anna Schroeder
Anna Schroeder is best known as the wife of Australian professional basketball player Matthew Dellavedova.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2cf6e29881908ddb8efca9a456a3 |
completed | April 14, 2026, 12:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbac89ebd48190ab448f74daf82a96 |
completed | May 6, 2026, 9:03 p.m. |
Created at: April 9, 2026, 10:17 p.m.