Triple
T29374971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aquaman #11 |
E744966
|
entity |
| Predicate | hasFutureRoleForCharacter |
P52440
|
FINISHED |
| Object | Mera becomes queen of Atlantis |
—
|
LITERAL 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: Mera becomes queen of Atlantis | Statement: [Aquaman #11, hasFutureRoleForCharacter, Mera becomes queen of Atlantis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFutureRoleForCharacter Context triple: [Aquaman #11, hasFutureRoleForCharacter, Mera becomes queen of Atlantis]
-
A.
characterFutureRole
chosen
Indicates the role or position that a character is expected or intended to assume at a later point in time.
-
B.
hasHumanCharacterRole
Indicates that an entity is assigned a role or function specifically associated with a human character within a context such as a story, performance, or representation.
-
C.
hasFictionalRole
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
-
D.
hasNamesakeRoleFor
Indicates that one entity holds a role or position that is named after, or serves as a namesake for, another entity.
-
E.
hasPlayedRole
Indicates that an entity has performed or portrayed a particular role or character in some context (such as a film, play, or production).
- F. None of above.
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_69f0a79ba954819094597628112c6091 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f669aca96081909c9b2aab89003f16 |
completed | May 2, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f66339175c819080bd70f0ff7057b1 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 2:30 p.m.