Triple
T5417650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweeney Todd (stage production) |
E121169
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object | Johanna |
E366888
|
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: Johanna | Statement: [Sweeney Todd (stage production), notableSong, Johanna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Johanna Context triple: [Sweeney Todd (stage production), notableSong, Johanna]
-
A.
Johanna
Johanna is the given name of Johanna Spyri, the Swiss author best known for creating the classic children's novel "Heidi."
-
B.
Johanna
chosen
"Johanna" is a recurring, lyrically poignant love song from Stephen Sondheim's musical *Sweeney Todd: The Demon Barber of Fleet Street*.
-
C.
Joanna
Joanna is the first name of Joanna Newsom, an American harpist, singer-songwriter, and musician known for her intricate compositions and distinctive vocal style.
-
D.
Joanna
Joanna is a woman mentioned in the New Testament as one of Jesus’ followers who witnessed his resurrection.
-
E.
Julianna
Julianna is a feminine given name most notably borne by American actress Julianna Margulies.
- 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_69bd463a41cc8190b32ff5af2b96ca93 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd87e620f081909eb9a5e1f284e5a2 |
completed | March 20, 2026, 5:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf4121edc4819081fdb79dcc182540 |
completed | March 22, 2026, 1:08 a.m. |
Created at: March 20, 2026, 2:05 p.m.