Triple
T16680758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Radak |
E405331
|
entity |
| Predicate | hasAcronym |
P43
|
FINISHED |
| Object | Radak |
E405331
|
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: Radak | Statement: [Radak, hasAcronym, Radak]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Radak Context triple: [Radak, hasAcronym, Radak]
-
A.
Radak
chosen
Radak, also known as Rabbi David Kimhi, was a prominent medieval Jewish biblical commentator, grammarian, and lexicographer whose works are central to traditional Jewish Bible study.
-
B.
Skalica
Skalica is a historic town in western Slovakia known for its well-preserved medieval center, traditional Skalický trdelník pastry, and location near the Czech border.
-
C.
Krasnobród
Krasnobród is a small town in southeastern Poland known for its historical role in World War II and as a local tourist and spa destination in the Roztocze region.
-
D.
Krosno
Krosno is a historic town in southeastern Poland known for its glassmaking industry and well-preserved old town.
-
E.
Bednja
Bednja is a river in northern Croatia that flows through the Zagorje region before joining the Drava River.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d6f5cf481909e7628bbaa884e5a |
completed | April 18, 2026, 12:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a404f448190a9dc7831382ffcdc |
completed | May 10, 2026, 1:38 p.m. |
Created at: April 10, 2026, 5:19 a.m.