Triple
T3196652
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Page |
E66950
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Jennifer Page
Jennifer Page is a pop singer best known for her late-1990s hit single "Crush."
|
E336012
|
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: Jennifer Page | Statement: [Page, hasNotableBearer, Jennifer Page]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jennifer Page Context triple: [Page, hasNotableBearer, Jennifer Page]
-
A.
Jennifer Wenger
Jennifer Wenger is an American actress and producer known for her work in genre films and television, as well as for her marriage to actor Casper Van Dien.
-
B.
Jennifer Lash
Jennifer Lash was a British novelist and painter known for her literary works and as the matriarch of the Fiennes acting family.
-
C.
Melissa Mathison
Melissa Mathison was an American screenwriter best known for writing the screenplay for Steven Spielberg’s film "E.T. the Extra-Terrestrial."
-
D.
Joanna Page
Joanna Page is a Welsh actress best known for her role as Stacey Shipman in the BBC sitcom "Gavin & Stacey."
-
E.
Jennifer Bradley
Jennifer Bradley is a Republican member of the Florida Senate known for sponsoring high-profile legislation, including the 2022 bill targeting the Reedy Creek Improvement District that affected Disney’s self-governing status.
- 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: Jennifer Page Triple: [Page, hasNotableBearer, Jennifer Page]
Generated description
Jennifer Page is a pop singer best known for her late-1990s hit single "Crush."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jennifer Page Target entity description: Jennifer Page is a pop singer best known for her late-1990s hit single "Crush."
-
A.
Jennifer Wenger
Jennifer Wenger is an American actress and producer known for her work in genre films and television, as well as for her marriage to actor Casper Van Dien.
-
B.
Jennifer Lash
Jennifer Lash was a British novelist and painter known for her literary works and as the matriarch of the Fiennes acting family.
-
C.
Melissa Mathison
Melissa Mathison was an American screenwriter best known for writing the screenplay for Steven Spielberg’s film "E.T. the Extra-Terrestrial."
-
D.
Joanna Page
Joanna Page is a Welsh actress best known for her role as Stacey Shipman in the BBC sitcom "Gavin & Stacey."
-
E.
Jennifer Bradley
Jennifer Bradley is a Republican member of the Florida Senate known for sponsoring high-profile legislation, including the 2022 bill targeting the Reedy Creek Improvement District that affected Disney’s self-governing status.
- 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_69ad8588ba18819086a10951c32ecb80 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada7177b488190b7a1b40ff3fae15f |
completed | March 8, 2026, 4:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b24bb2c9908190b3abc395537e22ac |
completed | March 12, 2026, 5:14 a.m. |
| NEDg | Description generation | batch_69b24cda28308190b33f189b8c7f3c58 |
completed | March 12, 2026, 5:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b24d84f29c819087c15fd3883d6657 |
completed | March 12, 2026, 5:22 a.m. |
Created at: March 8, 2026, 3:07 p.m.