Triple
T5110786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | J. K. Rowling |
E115208
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Joanne |
E274853
|
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: Joanne | Statement: [J. K. Rowling, givenName, Joanne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joanne Context triple: [J. K. Rowling, givenName, Joanne]
-
A.
Joanne
chosen
Joanne is a feminine given name of Hebrew origin, commonly used in English-speaking countries.
-
B.
Joanna
Joanna is a woman mentioned in the New Testament as one of Jesus’ followers who witnessed his resurrection.
-
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.
Judy
Judy was the Allied reporting name for the Japanese Yokosuka D4Y carrier-based dive bomber used by the Imperial Japanese Navy during World War II.
-
E.
Judy
"Judy" is a 2019 biographical drama film in which Renée Zellweger portrays legendary entertainer Judy Garland during her final years, a role that earned her widespread acclaim and major acting awards.
- 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_69bd4441d1648190a54a533895041987 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75ad362c8190b9cbded390aaea3c |
completed | March 20, 2026, 4:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bec372e308819082fefe9e2b58370d |
completed | March 21, 2026, 4:12 p.m. |
Created at: March 20, 2026, 1:41 p.m.