Triple
T4681435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johanna Spyri |
E103810
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Johanna |
E103810
|
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: [Johanna Spyri, hasGivenName, Johanna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Johanna Context triple: [Johanna Spyri, hasGivenName, Johanna]
-
A.
Johanna
chosen
Johanna is the given name of Johanna Spyri, the Swiss author best known for creating the classic children's novel "Heidi."
-
B.
Johanna
"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.
Julianna
Julianna is a feminine given name most notably borne by American actress Julianna Margulies.
-
E.
Yovanna
Yovanna is a fictional character played by actress Adria Arjona, known from her work in film and television.
- 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_69bd43debbf08190b4bc372e286ec234 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd636d306081908ff512896f54cb10 |
completed | March 20, 2026, 3:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be1056abf081908aadaea8d9f22860 |
completed | March 21, 2026, 3:28 a.m. |
Created at: March 20, 2026, 1:16 p.m.