Triple
T10810933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Me and Juliet |
E255096
|
entity |
| Predicate | originalCastMember |
P7010
|
FINISHED |
| Object | Joan McCracken |
E705467
|
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: Joan McCracken | Statement: [Me and Juliet, originalCastMember, Joan McCracken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joan McCracken Context triple: [Me and Juliet, originalCastMember, Joan McCracken]
-
A.
Joan McCracken
chosen
Joan McCracken was an American actress and dancer known for her comic talent and influential work in mid-20th-century Broadway musicals.
-
B.
Joan Murray
Joan Murray was the wife of famed British World War II flying ace and double amputee Sir Douglas Bader.
-
C.
Joan Hackett
Joan Hackett was an American actress known for her acclaimed work in film, television, and theater during the 1960s and 1970s, often portraying complex, intelligent female characters.
-
D.
Marie McKay
Marie McKay was the wife of Austrian-American actor Joseph Schildkraut, a prominent performer of stage and early Hollywood cinema.
-
E.
Joan Beck
Joan Beck was a writer and journalist who collaborated with pioneering anesthesiologist and neonatologist Virginia Apgar on works about childbirth and infant care.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733b7bfac8190b6ae34144376d6ad |
completed | April 9, 2026, 5:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76b9112948190a0dd747a67f8206a |
completed | May 3, 2026, 3:36 p.m. |
Created at: April 8, 2026, 9:18 p.m.