Triple
T17467003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miguel Bosé |
E425301
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Linda |
—
|
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: Linda | Statement: [Miguel Bosé, notableWork, Linda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linda Context triple: [Miguel Bosé, notableWork, Linda]
-
A.
Linda
chosen
"Linda" is a popular 1946 pop standard song closely associated with American singer Buddy Clark.
-
B.
Linda
Linda is a supporting character in the film "The Pursuit of Happyness," depicted as Chris Gardner’s struggling and increasingly distant partner amid the family’s financial hardships.
-
C.
Linda
Linda is a tragic, outcast figure in Aldous Huxley’s dystopian novel "Brave New World," whose experiences highlight the clash between the World State’s values and natural human emotion.
-
D.
Linda
Linda is an unincorporated community in Yuba County, California, known primarily as a residential area near the city of Marysville.
-
E.
Linda
Linda is a feminine given name of Germanic origin that became widely used in English-speaking countries in the 20th 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_69d889dbc2e88190b18ea6115e819258 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451a8f4908190a67a3a82a1c8f011 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:47 a.m.