Triple
T12232107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dark Avengers |
E291498
|
entity |
| Predicate | member |
P10
|
FINISHED |
| Object | Daken |
E438958
|
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: Daken | Statement: [Dark Avengers, member, Daken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daken Context triple: [Dark Avengers, member, Daken]
-
A.
Daken
chosen
Daken is a fictional Marvel Comics antihero and mutant, best known as the son of Wolverine with retractable claws and a complex, morally ambiguous personality.
-
B.
Kallocain
Kallocain is a dystopian science fiction novel by Swedish author Karin Boye that portrays a totalitarian surveillance state and the psychological effects of absolute control.
-
C.
Darek
Darek is a given name, typically a variant spelling of Derek used in various European countries.
-
D.
Djo
Djo is the psychedelic rock and synth-pop musical project of American actor and musician Joe Keery.
-
E.
Durkan
Durkan is a surname most notably associated with Jenny Durkan, the former mayor of Seattle and an American attorney and politician.
- 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91ca45bd48190b8b7f6b29b6bb25b |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60aad2d488190ba36588e3376ca1a |
completed | May 2, 2026, 2:31 p.m. |
Created at: April 8, 2026, 9:51 p.m.