Triple
T12911558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trigon |
E308875
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Arella |
E1014616
|
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: Arella | Statement: [Trigon, spouse, Arella]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arella Context triple: [Trigon, spouse, Arella]
-
A.
Arella
chosen
Arella is a character in DC Comics, best known as the human mother of the Teen Titans member Raven and a former acolyte of the interdimensional demon Trigon.
-
B.
Amorina
Amorina is a 19th-century Swedish novel by Carl Jonas Love Almqvist, known for its romantic and psychological depth within early modern Swedish literature.
-
C.
Sylvana
Sylvana is a feminine given name, often considered a variant of Silvana, typically associated with meanings related to forests or woodland.
-
D.
Gessa
Gessa is a small village in the Val d'Aran region of Catalonia, Spain, known for its traditional Pyrenean architecture and mountain setting.
-
E.
Azara
Azara is a suburban locality on the outskirts of Guwahati in Assam, India, known for hosting the city's main international airport and related transport infrastructure.
- 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9719f96248190b746f9d4a468560c |
completed | April 10, 2026, 9:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c0e7e9fc8190ad065a587c6c45dd |
completed | May 3, 2026, 3:28 a.m. |
Created at: April 9, 2026, 5:41 p.m.