Triple
T6976334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camila Cabello |
E161725
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Karla |
E243971
|
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: Karla | Statement: [Camila Cabello, givenName, Karla]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karla Context triple: [Camila Cabello, givenName, Karla]
-
A.
Karla
chosen
Karla is the elusive Soviet spymaster and primary antagonist of John le Carré’s George Smiley novels, symbolizing the Cold War espionage rivalry between British intelligence and the KGB.
-
B.
Jeremiah Valeska
Jeremiah Valeska is a major antagonist in the TV series "Gotham," known as one of the show's Joker-inspired villains and the twin brother of Jerome Valeska.
-
C.
Corina
Corina is a feminine given name used in various cultures, often considered a variant of names like Corine or Corinna.
-
D.
Karin
Karin is a feminine given name used in various cultures, often considered a variant of names like Karen or Katherine.
-
E.
Carla
Carla is a feminine given name commonly used in various languages, often considered the female form of Carl or Charles.
- 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_69c68854a0d88190bc0bf82263f1afce |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db677bbc8190a084b6951e5c3182 |
completed | March 27, 2026, 7:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c761ab41b0819084d26c10bb763f8e |
completed | March 28, 2026, 5:05 a.m. |
Created at: March 27, 2026, 2:31 p.m.