Triple
T3205264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Jackson |
E67145
|
entity |
| Predicate | associatedWithAlbum |
P22755
|
FINISHED |
| Object | Janet. |
E74976
|
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: Janet. | Statement: [Miss Jackson, associatedWithAlbum, Janet.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Janet. Context triple: [Miss Jackson, associatedWithAlbum, Janet.]
-
A.
Janet
chosen
Janet is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
-
B.
Janice
Janice is a feminine given name commonly used in English-speaking countries.
-
C.
Jeanie
Jeanie is a female given name, often used as a diminutive of Jean or Jeanne.
-
D.
Janet McQueen
Janet McQueen is a sibling of the renowned British fashion designer Alexander McQueen.
-
E.
Jeane
Jeane is a feminine given name most notably associated with American diplomat and political scientist Jeane Kirkpatrick.
- 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_69ad8589bd988190afa7ed2bdffb7b33 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaa559848819082d1e61f586278dd |
completed | March 8, 2026, 4:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e822b64c8190b053234690841d38 |
completed | March 12, 2026, 4:21 p.m. |
Created at: March 8, 2026, 3:07 p.m.