Triple
T15558279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JoAnna Garcia |
E370927
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | JoAnna |
E1155847
|
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: JoAnna | Statement: [JoAnna Garcia, givenName, JoAnna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: JoAnna Context triple: [JoAnna Garcia, givenName, JoAnna]
-
A.
Johanna
Johanna is a Hungarian experimental opera film reimagining the story of Joan of Arc in a modern hospital setting, directed by Kornél Mundruczó.
-
B.
Johanna
chosen
Johanna is a feminine given name of Hebrew origin, commonly used in many European languages and derived from a form of "Johannes" meaning "God is gracious."
-
C.
Johanna
Johanna is the given name of Johanna Spyri, the Swiss author best known for creating the classic children's novel "Heidi."
-
D.
Johanna
"Johanna" is a recurring, lyrically poignant love song from Stephen Sondheim's musical *Sweeney Todd: The Demon Barber of Fleet Street*.
-
E.
Johanna
Johanna is the birth name of Magda Goebbels, the wife of Nazi propaganda minister Joseph Goebbels and a prominent figure in Nazi Germany.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04dda3ab88190ab383333ce69fe8f |
completed | April 16, 2026, 2:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff456635588190a2473bcff3ae4a53 |
completed | May 9, 2026, 2:32 p.m. |
Created at: April 10, 2026, 4:09 a.m.