Triple
T18332479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grete Samsa |
E439179
|
entity |
| Predicate | hasSibling |
P363
|
FINISHED |
| Object | Gregor Samsa |
—
|
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 Samsa | Statement: [Grete Samsa, hasSibling, Gregor Samsa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gregor Samsa Context triple: [Grete Samsa, hasSibling, Gregor Samsa]
-
A.
Gregor Samsa
chosen
Gregor Samsa is the beleaguered traveling salesman who famously awakens transformed into a giant insect in Franz Kafka’s novella "The Metamorphosis."
-
B.
Gregor
Gregor is a masculine given name of Latin origin, commonly associated with figures such as the pioneering geneticist Gregor Mendel.
-
C.
Grete Samsa
Grete Samsa is Gregor Samsa’s sister in Franz Kafka’s novella "The Metamorphosis," whose initial compassion gradually turns to rejection as his transformation isolates him from his family.
-
D.
Gregor de Berghmann
Gregor de Berghmann is a fictional character appearing in the narrative of "The Black Room."
-
E.
Peter Schlemihl
Peter Schlemihl is the fictional protagonist of Adelbert von Chamisso’s novella, known for selling his shadow to the Devil and suffering the social and existential consequences of this bargain.
- 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_69d8b9175fec8190af865699b4e64d8c |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50ecaf6f48190ae7547cc0f8e6efa |
completed | April 19, 2026, 5:20 p.m. |
Created at: April 10, 2026, 10:36 a.m.