Triple
T20255451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koko |
E498682
|
entity |
| Predicate | trainer |
P41095
|
FINISHED |
| Object | Nelson Woss |
—
|
NE NERFINISHED |
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: Nelson Woss | Statement: [Koko, trainer, Nelson Woss]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nelson Woss Context triple: [Koko, trainer, Nelson Woss]
-
A.
Nelson Woss
chosen
Nelson Woss is an Australian film producer best known for his work on the popular family film "Red Dog" and its related projects.
-
B.
Nelson McDowell
Nelson McDowell was an American character actor of the silent and early sound film era, known for his distinctive gaunt appearance and frequent roles in Westerns and serials.
-
C.
Walter Nelson
Walter Nelson was an attorney who served on the defense team in the landmark Ossian Sweet murder trial, which challenged racial injustice in 1920s Detroit.
-
D.
Nelson Emerson
Nelson Emerson is a Canadian former professional ice hockey forward who played over a decade in the NHL for multiple teams and later became an executive and development coach.
-
E.
John Nelson
John Nelson is a central fictional figure in the Western-themed narrative of "Kansas Pacific," around whom much of the story's action and conflict revolves.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e673ab60388190be32cc69bf2b6f76 |
completed | April 20, 2026, 6:42 p.m. |
Created at: April 11, 2026, 11:41 p.m.