Triple
T8666798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olli Wisdom |
E205695
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Olli Wisdom |
E205695
|
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: Olli Wisdom | Statement: [Olli Wisdom, name, Olli Wisdom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Olli Wisdom Context triple: [Olli Wisdom, name, Olli Wisdom]
-
A.
Olli Wisdom
chosen
Olli Wisdom was a British musician and DJ best known as a pioneering figure in the psychedelic trance scene and frontman of the gothic rock band Specimen.
-
B.
Jack Wisdom
Jack Wisdom is an American planetary scientist and MIT professor known for his work on celestial mechanics and dynamical chaos in the solar system.
-
C.
Jack Oliver
Jack Oliver was an influential American geophysicist whose work on plate tectonics and seismic studies helped revolutionize our understanding of Earth's structure.
-
D.
Jerry Wisdom
Jerry Wisdom was a Bahamian sprinter known for competing in international track and field events, including the Olympic Games.
-
E.
Tom Wisdom
Tom Wisdom is a British actor known for his roles in films like "300" and various television dramas.
- 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_69ca83516ae88190aefe034b3bc589e3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc48a34b808190aa9aed9cdb2900e6 |
completed | March 31, 2026, 10:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cecd1592788190a882fb7218f95807 |
completed | April 2, 2026, 8:09 p.m. |
Created at: March 30, 2026, 6:31 p.m.