Triple
T4757143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thanatos |
E105615
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Nemesis |
E144401
|
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: Nemesis | Statement: [Thanatos, sibling, Nemesis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nemesis Context triple: [Thanatos, sibling, 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 novel by Philip Roth that explores themes of fate, guilt, and moral responsibility through the story of a polio outbreak in 1940s Newark.
-
C.
The Fury
The Fury is a 1978 supernatural horror-thriller film directed by Brian De Palma, known for its intense psychic powers storyline and stylized violence.
-
D.
Grimus
Grimus is Salman Rushdie’s debut novel, a genre-blending work of science fiction and fantasy that explores themes of identity, immortality, and exile.
-
E.
Aegitna
Aegitna is the ancient name of the city now known as Cannes on the French Riviera.
- 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_69bd43f14cac819081c7c69803648211 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64ec16a0819089836e4388b555f6 |
completed | March 20, 2026, 3:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be3a72ba908190ad9b423aea2a22b8 |
completed | March 21, 2026, 6:28 a.m. |
Created at: March 20, 2026, 1:20 p.m.