Triple
T6812861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Long Night |
E156677
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Jo Ann
Jo Ann is a fictional character appearing in the 1947 film noir drama "The Long Night."
|
E622398
|
NE FINISHED |
How this triple was built (4 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: Jo Ann | Statement: [The Long Night, character, Jo Ann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jo Ann Context triple: [The Long Night, character, Jo Ann]
-
A.
Beverlee McKinsey
Beverlee McKinsey was a highly acclaimed American soap opera actress best known for her powerful, sophisticated portrayals on daytime dramas such as Another World and Guiding Light.
-
B.
Jeane
Jeane is a feminine given name most notably associated with American diplomat and political scientist Jeane Kirkpatrick.
-
C.
Linda May
Linda May is a real-life modern nomad who appears as herself in the acclaimed film "Nomadland," representing the community of American van-dwellers and itinerant workers.
-
D.
Sonja Hogg
Sonja Hogg is an American women's basketball coach best known for helping build Baylor University's women's program into a national contender.
-
E.
Georgia Groome
Georgia Groome is an English actress best known for her lead role in the teen comedy film "Angus, Thongs and Perfect Snogging."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Jo Ann Triple: [The Long Night, character, Jo Ann]
Generated description
Jo Ann is a fictional character appearing in the 1947 film noir drama "The Long Night."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jo Ann Target entity description: Jo Ann is a fictional character appearing in the 1947 film noir drama "The Long Night."
-
A.
Beverlee McKinsey
Beverlee McKinsey was a highly acclaimed American soap opera actress best known for her powerful, sophisticated portrayals on daytime dramas such as Another World and Guiding Light.
-
B.
Jeane
Jeane is a feminine given name most notably associated with American diplomat and political scientist Jeane Kirkpatrick.
-
C.
Linda May
Linda May is a real-life modern nomad who appears as herself in the acclaimed film "Nomadland," representing the community of American van-dwellers and itinerant workers.
-
D.
Sonja Hogg
Sonja Hogg is an American women's basketball coach best known for helping build Baylor University's women's program into a national contender.
-
E.
Georgia Groome
Georgia Groome is an English actress best known for her lead role in the teen comedy film "Angus, Thongs and Perfect Snogging."
- F. None of above. chosen
Provenance (5 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_69c68828b26c819090fe9df7612bbc27 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d329861881909f65bd1017ea384b |
completed | March 27, 2026, 6:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723da8fe08190b507e569a2511f5a |
completed | March 28, 2026, 12:42 a.m. |
| NEDg | Description generation | batch_69c7266273fc8190acd2797981d3ca63 |
completed | March 28, 2026, 12:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c726c382308190ba3fe630f90b3d38 |
completed | March 28, 2026, 12:54 a.m. |
Created at: March 27, 2026, 2:17 p.m.