Triple
T22857902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbie franchise |
E566833
|
entity |
| Predicate | hasSetting |
P3538
|
FINISHED |
| Object | Malibu |
—
|
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: Malibu | Statement: [Barbie franchise, hasSetting, Malibu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malibu Context triple: [Barbie franchise, hasSetting, Malibu]
-
A.
Malibu
Malibu is a popular coconut-flavored Caribbean rum liqueur widely used in tropical and mixed cocktails.
-
B.
Malibu, California
chosen
Malibu, California is a coastal city in Los Angeles County known for its scenic beaches, affluent residential communities, and role as a hub for entertainment industry professionals.
-
C.
Malibu Shores
Malibu Shores is a short-lived 1990s American teen drama television series that followed the lives and relationships of affluent high school students in a Southern California beach community.
-
D.
Dellaventura
Dellaventura is a 1990s American crime drama television series starring Danny Aiello as a former NYPD detective turned private investigator.
-
E.
La Elipa
La Elipa is a Madrid Metro station in the Ciudad Lineal district, serving the residential neighborhood of the same name on Line 2.
- 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_69e24589083081908d5694c4fdc80086 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17ebe3f9c8190a864f4e84dc7795d |
completed | April 29, 2026, 3:45 a.m. |
Created at: April 17, 2026, 3:37 p.m.