Triple
T22168906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacGregor |
E547866
|
entity |
| Predicate | patronymicFrom |
P7966
|
FINISHED |
| Object | Gregor |
—
|
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: Gregor | Statement: [MacGregor, patronymicFrom, Gregor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gregor Context triple: [MacGregor, patronymicFrom, Gregor]
-
A.
Gregor
chosen
Gregor is a masculine given name of Latin origin, commonly associated with figures such as the pioneering geneticist Gregor Mendel.
-
B.
Gregor Samsa
Gregor Samsa is the beleaguered traveling salesman who famously awakens transformed into a giant insect in Franz Kafka’s novella "The Metamorphosis."
-
C.
Gregor Jordan
Gregor Jordan is an Australian film director and screenwriter known for darkly comedic and politically charged films such as "Two Hands," "Buffalo Soldiers," and "Unthinkable."
-
D.
Gregor de Berghmann
Gregor de Berghmann is a fictional character appearing in the narrative of "The Black Room."
-
E.
Mr. Samsa
Mr. Samsa is Gregor Samsa’s domineering and often hostile father in Franz Kafka’s novella "The Metamorphosis."
- 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_69e11e3c4c5c81908d336165816b12e0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12a6721e8819081d732df2691f4a4 |
completed | April 28, 2026, 9:45 p.m. |
Created at: April 16, 2026, 8:34 p.m.