Triple
T4650825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sebastian Thrun |
E102289
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Thrun |
E102289
|
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: Thrun | Statement: [Sebastian Thrun, hasSurname, Thrun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thrun Context triple: [Sebastian Thrun, hasSurname, Thrun]
-
A.
Thrun
chosen
Thrun is the surname of Sebastian Thrun, a prominent computer scientist and robotics expert known for his work in self-driving cars and artificial intelligence.
-
B.
Rover
Rover is a historic British automotive marque and former manufacturer known for producing a range of passenger cars and engines throughout the 20th century.
-
C.
Botley
Botley is a historic village and civil parish in Hampshire, England, known for its rural character and location near the River Hamble.
-
D.
Botley
Botley is a village and suburb on the western edge of Oxford, England, known for its residential character and proximity to the city.
-
E.
Kismet
Kismet is a 1955 MGM musical fantasy film directed by Vincente Minnelli, adapted from the Broadway musical set in a stylized, exoticized Baghdad.
- 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_69bd43d71a308190afea7280841b0de8 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd6302078081909451589d39c7b28c |
completed | March 20, 2026, 3:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be0374967c8190b77bcd3ea1c4d59d |
completed | March 21, 2026, 2:33 a.m. |
Created at: March 20, 2026, 1:14 p.m.