Triple
T15023631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rudolphine Tables |
E378147
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object | Johannes Kepler |
E12150
|
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: Johannes Kepler | Statement: [Rudolphine Tables, author, Johannes Kepler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Johannes Kepler Context triple: [Rudolphine Tables, author, Johannes Kepler]
-
A.
Johannes Kepler
chosen
Johannes Kepler was a pioneering 17th-century German astronomer and mathematician best known for formulating the three laws of planetary motion that laid crucial groundwork for classical mechanics.
-
B.
Képler
Képler is a given name associated with the individual known as Pepe.
-
C.
Abraham Brahe
Abraham Brahe was a Swedish nobleman of the influential Brahe family and the father of statesman and governor-general Per Brahe the Younger.
-
D.
Tycho Brahe
Tycho Brahe was a Danish nobleman and astronomer whose precise naked-eye observations of the heavens greatly improved astronomical data and paved the way for Kepler’s laws of planetary motion.
-
E.
Jørgen Brahe
Jørgen Brahe was a Danish nobleman and foster father of the astronomer Tycho Brahe, playing a key role in raising and educating him.
- 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7de117c8190a1b9fa8d1602057e |
completed | April 15, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d39a0908190a27f7bbaee7a04ef |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 2:56 a.m.