Triple
T9968553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arthur Curry |
E195743
|
entity |
| Predicate | family |
P566
|
FINISHED |
| Object | Atlanna |
E746331
|
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: Atlanna | Statement: [Arthur Curry, family, Atlanna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Atlanna Context triple: [Arthur Curry, family, Atlanna]
-
A.
Atlanna
chosen
Atlanna is the Atlantean queen and mother of Aquaman, known for bridging the worlds of land and sea in DC's Aquaman films.
-
B.
Everina
Everina Wollstonecraft was an 18th-century English governess and writer, best known as the younger sister of feminist philosopher Mary Wollstonecraft.
-
C.
Altilia
Altilia is the modern Italian village that encompasses the archaeological remains of the ancient Roman town of Saepinum in the Molise region.
-
D.
Lelylaan
Lelylaan is a transport hub and railway/metro station in Amsterdam’s Nieuw-West district, connecting metro, train, tram, and bus services.
-
E.
Velda
Velda is the loyal and resourceful secretary and love interest of private investigator Mike Hammer in the hardboiled crime novel and film "Kiss Me Deadly."
- 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_69ca82ebd1288190912f9e4482d1fa35 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb7b683ac8190ac97bd775a860d29 |
completed | April 2, 2026, 12:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d23db701b881909bb986a32df4349b |
completed | April 5, 2026, 10:47 a.m. |
Created at: March 30, 2026, 8:47 p.m.