Triple
T20188595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fritz Schumacher |
E492925
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Fritz |
—
|
NE NERFINISHED |
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: Fritz | Statement: [Fritz Schumacher, givenName, Fritz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fritz Context triple: [Fritz Schumacher, givenName, Fritz]
-
A.
Fritz
Fritz is an individual known primarily as the offspring of Fifi.
-
B.
Fritz
Fritz is the hunchbacked assistant to Dr. Frankenstein in the 1931 horror film "Frankenstein," known for helping to procure the monster’s body parts and brain.
-
C.
Fritz
chosen
Fritz is a masculine given name of German origin commonly used in German-speaking countries.
-
D.
Fritz
Fritz is one of the animatronic macaw hosts in Walt Disney’s Enchanted Tiki Room attraction at Disney theme parks.
-
E.
Fritz
Fritz is a comedic monster character from the animated series "Monsters at Work," known for his role as the enthusiastic and quirky supervisor of the MIFT maintenance team at Monsters, Inc.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad404508190981cfb7cab18d8d3 |
completed | April 20, 2026, 6:05 p.m. |
Created at: April 11, 2026, 11:37 p.m.