Triple
T13525213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Everclear |
E322999
|
entity |
| Predicate | member |
P10
|
FINISHED |
| Object | Greg Eklund |
E346163
|
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: Greg Eklund | Statement: [Everclear, member, Greg Eklund]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greg Eklund Context triple: [Everclear, member, Greg Eklund]
-
A.
Greg Eklund
chosen
Greg Eklund is an American drummer best known for his work with the alternative rock band Everclear.
-
B.
Michael Eklund
Michael Eklund is a Canadian character actor known for his intense, often villainous roles in film and television thrillers.
-
C.
Erik Christensen
Erik Christensen is a retired Canadian professional ice hockey centre who played in the NHL for several teams, including the Pittsburgh Penguins and New York Rangers.
-
D.
Jeffrey Nordling
Jeffrey Nordling is an American actor known for his work in television dramas and films, often portraying complex professional and family-man characters.
-
E.
Jon Ekstrand
Jon Ekstrand is a Swedish film composer and sound designer known for his atmospheric scores for documentaries and feature films, including collaborations with director Daniel Espinosa.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafa6ad60819087824e4ac83934ed |
completed | April 12, 2026, 2:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7a838581c819092a195f60673b743 |
completed | May 3, 2026, 7:55 p.m. |
Created at: April 9, 2026, 9:44 p.m.