Triple
T21256294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lesley Selander |
E523877
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Les Selander |
—
|
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: Les Selander | Statement: [Lesley Selander, alsoKnownAs, Les Selander]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Les Selander Context triple: [Lesley Selander, alsoKnownAs, Les Selander]
-
A.
Selander
chosen
Selander is a surname most notably associated with American film director Lesley Selander, known for his prolific work in Westerns.
-
B.
Gyllensten
Gyllensten is a Swedish surname most notably associated with Lars Gyllensten, a prominent author and former member of the Swedish Academy.
-
C.
Bollestad
Bollestad is a Norwegian surname most notably associated with politician Olaug Bollestad.
-
D.
Somerhalder
Somerhalder is the surname of American actor, director, and environmental activist Ian Somerhalder, best known for his role in the television series "The Vampire Diaries."
-
E.
Ekornes
Ekornes is a Norwegian furniture manufacturer best known for its Stressless line of reclining chairs and sofas.
- 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_69e0b5146c108190adc9adb73e90abff |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e735a1f9e08190b494f582bcae5c35 |
completed | April 21, 2026, 8:30 a.m. |
Created at: April 16, 2026, 3:58 p.m.