Triple
T21949690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Môme Pistache |
E542030
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Lilo |
—
|
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: Lilo | Statement: [La Môme Pistache, portrayedBy, Lilo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lilo Context triple: [La Môme Pistache, portrayedBy, Lilo]
-
A.
Lilo
chosen
Lilo is a French singer known for her interpretation of classic songs, including the standard "It's All Right with Me."
-
B.
Lilo Pelekai
Lilo Pelekai is a young Hawaiian girl from Disney's "Lilo & Stitch," known for her quirky personality, love of Elvis Presley, and close bond with her alien "dog" Stitch.
-
C.
Lilo Baur
Lilo Baur is a Swiss actress and theatre director known for her work in European film, television, and stage productions.
-
D.
Aulani
Aulani is a Disney-operated Hawaiian resort and spa that blends family-friendly entertainment with local Hawaiian culture and storytelling.
-
E.
Lolei
Lolei is an ancient temple in Cambodia’s Angkor region, known as one of the Roluos Group of early Khmer brick towers built during the late 9th century.
- 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_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1243aed048190b4342899c83b38ec |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:58 p.m.