Triple
T1297513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Something Fresh |
E27686
|
entity |
| Predicate | hasMainCharacter |
P1183
|
FINISHED |
| Object |
Joan Valentine
Joan Valentine is a quick-witted, resourceful young woman who works as a journalist and adventurer in P. G. Wodehouse’s comic fiction.
|
E152728
|
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: Joan Valentine | Statement: [Something Fresh, hasMainCharacter, Joan Valentine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joan Valentine Context triple: [Something Fresh, hasMainCharacter, Joan Valentine]
-
A.
Audrey Callaghan
Audrey Callaghan was a British charity worker and public figure, known for her extensive work in children's welfare and for being the wife of UK Prime Minister James Callaghan.
-
B.
Vivian Lake Brady
Vivian Lake Brady is the daughter of NFL quarterback Tom Brady and supermodel Gisele Bündchen.
-
C.
Faye Emerson
Faye Emerson was an American film and stage actress who became a popular early television personality in the 1940s and 1950s.
-
D.
Rachel Marron
Rachel Marron is a famous pop singer and actress who becomes the client and love interest of a former Secret Service agent in the romantic thriller film "The Bodyguard."
-
E.
Claricia Scotti
Claricia Scotti was a medieval Italian noblewoman known primarily as the mother of Pope Innocent III.
- 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: Joan Valentine Triple: [Something Fresh, hasMainCharacter, Joan Valentine]
Generated description
Joan Valentine is a quick-witted, resourceful young woman who works as a journalist and adventurer in P. G. Wodehouse’s comic fiction.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Joan Valentine Target entity description: Joan Valentine is a quick-witted, resourceful young woman who works as a journalist and adventurer in P. G. Wodehouse’s comic fiction.
-
A.
Audrey Callaghan
Audrey Callaghan was a British charity worker and public figure, known for her extensive work in children's welfare and for being the wife of UK Prime Minister James Callaghan.
-
B.
Vivian Lake Brady
Vivian Lake Brady is the daughter of NFL quarterback Tom Brady and supermodel Gisele Bündchen.
-
C.
Faye Emerson
Faye Emerson was an American film and stage actress who became a popular early television personality in the 1940s and 1950s.
-
D.
Rachel Marron
Rachel Marron is a famous pop singer and actress who becomes the client and love interest of a former Secret Service agent in the romantic thriller film "The Bodyguard."
-
E.
Claricia Scotti
Claricia Scotti was a medieval Italian noblewoman known primarily as the mother of Pope Innocent III.
- 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_69a496d6682881909ba658f1c1e0e2b0 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0f6bc90819094cad5d62550ea19 |
completed | March 1, 2026, 10:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acbf243adc8190b8516554701b4290 |
completed | March 8, 2026, 12:13 a.m. |
| NEDg | Description generation | batch_69acc2dc5c4c8190b6ba418aaacd1101 |
completed | March 8, 2026, 12:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69acc3ba816081908892101de3bfbf3e |
completed | March 8, 2026, 12:32 a.m. |
Created at: March 1, 2026, 7:51 p.m.