Triple
T9836684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blonde Venus |
E239118
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | W. Franke Harling |
E426106
|
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: W. Franke Harling | Statement: [Blonde Venus, musicBy, W. Franke Harling]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: W. Franke Harling Context triple: [Blonde Venus, musicBy, W. Franke Harling]
-
A.
W. Franke Harling
chosen
W. Franke Harling was an American composer best known for his film scores during the early sound era of Hollywood.
-
B.
William Wendt
William Wendt was a prominent American landscape painter celebrated as a leading figure of the California Impressionist movement.
-
C.
Harold Huth
Harold Huth was a British film director, producer, and occasional actor active in the mid-20th century, known for his work in the British studio system.
-
D.
George Hildebrand
George Hildebrand was an American Major League Baseball umpire active in the early 20th century.
-
E.
William Haade
William Haade was an American character actor known for his tough-guy roles in numerous Hollywood films from the 1930s through the 1950s.
- 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_69ca84e314108190978324a4bdb959f8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb33b07688190b78a70cf535c3efc |
completed | April 2, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b5aab5408190aacdc310222bb85b |
completed | April 5, 2026, 7:19 p.m. |
Created at: March 30, 2026, 8:33 p.m.