Triple
T23218179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HWV 34 |
E580807
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Morgana |
—
|
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: Morgana | Statement: [HWV 34, character, Morgana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morgana Context triple: [HWV 34, character, Morgana]
-
A.
Morgana
Morgana is the main villain in Disney's "The Little Mermaid II: Return to the Sea," a sea witch and Ursula's vengeful sister who seeks control over the ocean.
-
B.
Morgana
chosen
Morgana is a central antagonist and powerful sorceress in the BBC fantasy drama "Merlin," known for her complex transformation from ally to enemy of Camelot.
-
C.
Morgana Jones
Morgana Jones is a musical artist known for releasing tracks such as “She Believes in Me.”
-
D.
Demona
Demona is a central antagonist in Disney's animated series "Gargoyles," a powerful and vengeful gargoyle who harbors a deep hatred for humans.
-
E.
Queen of Blood (Nimue)
Queen of Blood (Nimue) is a powerful, malevolent sorceress and primary antagonist in the Hellboy universe, often depicted as a resurrected witch-queen whose actions threaten to bring about the end of the world.
- 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_69e2460389408190be74f41d217799a9 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1916653f08190a7dcbc659c6b6a25 |
completed | April 29, 2026, 5:04 a.m. |
Created at: April 17, 2026, 4:08 p.m.