Triple
T16078973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joanna Kerns |
E390049
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Joanna |
E695409
|
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 Kerns, givenName, Joanna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joanna Context triple: [Joanna Kerns, givenName, Joanna]
-
A.
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.
-
B.
Joanna
Joanna is a woman mentioned in the New Testament as one of Jesus’ followers who witnessed his resurrection.
-
C.
Joanna
chosen
Joanna is a feminine given name used in various cultures, often associated with forms of the name John and shared by many notable historical and contemporary figures.
-
D.
Joanna
Joanna is a serif typeface designed by British artist and typographer Eric Gill, known for its elegant, humanist letterforms and use in book typography.
-
E.
Joanna
Joanna is a key character in the cult-classic comedy film "Office Space," known as the friendly waitress who becomes the love interest of the protagonist.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e183c401a881908fcb0b753d2dfc8a |
completed | April 17, 2026, 12:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff798c2a48190b6eccd476a0a396f |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 4:57 a.m.