Triple
T11403833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | How to Handle a Woman |
E270183
|
entity |
| Predicate | composer |
P1361
|
FINISHED |
| Object | Frederick Loewe |
E240518
|
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: Frederick Loewe | Statement: [How to Handle a Woman, composer, Frederick Loewe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frederick Loewe Context triple: [How to Handle a Woman, composer, Frederick Loewe]
-
A.
Frederick Loewe
chosen
Frederick Loewe was a German-American composer best known for his classic Broadway and film musicals, including "My Fair Lady," "Camelot," and "Brigadoon."
-
B.
Bernard Newman
Bernard Newman was an American costume designer best known for his glamorous work in 1930s Hollywood musicals and films.
-
C.
Alan Jay Lerner
Alan Jay Lerner was an American lyricist and librettist best known for his collaborations with composer Frederick Loewe on classic Broadway and film musicals such as "My Fair Lady" and "Camelot."
-
D.
Harold Rome
Harold Rome was an American composer and lyricist best known for his work on Broadway musicals and film scores in the mid-20th century.
-
E.
Jule Styne
Jule Styne was a prolific American composer best known for his Broadway and film musical scores, including classics like "Gypsy" and "Funny Girl."
- 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_69d6aaddeaa8819088b30ef7b50598c9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8014ab46881909fa1d425926c617b |
completed | April 9, 2026, 7:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f165cc34608190b6a00aa120199eff |
completed | April 29, 2026, 1:58 a.m. |
Created at: April 8, 2026, 9:34 p.m.