Triple
T4666237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joost |
E102852
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Jost |
E405988
|
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: Jost | Statement: [Joost, relatedName, Jost]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jost Context triple: [Joost, relatedName, Jost]
-
A.
Modrow
Modrow is a German surname most notably associated with Hans Modrow, the last communist premier of East Germany.
-
B.
Jost Vacano
chosen
Jost Vacano is a German cinematographer renowned for his dynamic, technically innovative work on films such as "Das Boot," "RoboCop," and other major international productions.
-
C.
Eitel
Eitel is the introspective, spiritually searching protagonist of Norman Mailer’s novel "The Deer Park."
-
D.
Martz
Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
-
E.
Fiser
Fiser is a surname variant of Fischer, commonly associated with Central or Eastern European origins.
- 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_69bd43d9cba4819086c1ab1c2d9d2133 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd633d87788190a3c8946ed6995062 |
completed | March 20, 2026, 3:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be0384a1488190a59dc08766f526dd |
completed | March 21, 2026, 2:33 a.m. |
Created at: March 20, 2026, 1:15 p.m.