Triple
T16300061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avrom Sutzkever |
E395759
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Di festung |
E103433
|
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: Di festung | Statement: [Avrom Sutzkever, notableWork, Di festung]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Di festung Context triple: [Avrom Sutzkever, notableWork, Di festung]
-
A.
The Fortress
The Fortress is a South Korean historical drama film depicting the Joseon court’s struggle for survival during the Qing invasion, directed by Hwang Dong-hyuk.
-
B.
The Fortress
The Fortress is a popular nickname for MAPFRE Stadium, the historic soccer-specific home of the Columbus Crew in Major League Soccer.
-
C.
Das Schloss
Das Schloss is a prominent shopping mall in Berlin known for its distinctive architecture and wide range of retail and dining options.
-
D.
The Castle
chosen
The Castle is a surreal, unfinished novel by Franz Kafka that follows a land surveyor’s futile attempts to gain access to a mysterious, bureaucratic authority that governs a remote village.
-
E.
The Castle
The Castle is a historic government building in Jamestown that serves as a key administrative and architectural landmark of the area.
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e31c9e8819094593f3aeb44f2ca |
completed | April 17, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f9d7ef48190b7acebebcb9608c3 |
completed | May 10, 2026, 6:03 a.m. |
Created at: April 10, 2026, 5:06 a.m.