Triple
T19863149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dike |
E477320
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Nemesis |
—
|
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: Nemesis | Statement: [Dike, associatedWith, Nemesis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nemesis Context triple: [Dike, associatedWith, Nemesis]
-
A.
Nemesis
chosen
Nemesis is the Greek goddess of retribution and divine justice, known for punishing hubris and restoring moral balance.
-
B.
Nemesis
Nemesis is a towering, bioengineered monster from the Resident Evil franchise, known for relentlessly hunting survivors with heavy weaponry and near-invulnerable strength.
-
C.
Nemesis
Nemesis is a creator-owned comic book series by Mark Millar that follows a brilliant, sadistic supervillain who wages war on law enforcement.
-
D.
Nemesis
Nemesis is the European title of the classic side-scrolling space shooter game from Konami’s Gradius series.
-
E.
Nemesis
Nemesis is a renowned steel inverted roller coaster at Alton Towers Resort in the UK, famous for its intense, high-speed inversions and immersive alien-themed design.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6589c4c0081908cd51ff75441e7ac |
completed | April 20, 2026, 4:47 p.m. |
Created at: April 10, 2026, 1:51 p.m.