Triple
T14358634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kissing Jessica Stein |
E356037
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Heather Juergensen
Heather Juergensen is an American actress and writer best known for co-writing and starring in the indie romantic comedy film "Kissing Jessica Stein."
|
E1258810
|
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: Heather Juergensen | Statement: [Kissing Jessica Stein, screenwriter, Heather Juergensen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heather Juergensen Context triple: [Kissing Jessica Stein, screenwriter, Heather Juergensen]
-
A.
Lisa Gottsegen
Lisa Gottsegen is an American businesswoman and philanthropist best known as the longtime wife of actor Dustin Hoffman.
-
B.
Kimberly Schlapman
Kimberly Schlapman is an American country singer best known as a founding member and vocalist of the Grammy-winning group Little Big Town.
-
C.
Heather Faulkiner
Heather Faulkiner is known as the wife of prominent American sportscaster Marv Albert.
-
D.
Heather Persons
Heather Persons is a film editor best known for her work on the independent comedy-drama "Sunshine Cleaning."
-
E.
Denise Huth
Denise Huth is a television producer best known for her long-running work as an executive producer on AMC’s The Walking Dead franchise and its related spin-offs.
- 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: Heather Juergensen Triple: [Kissing Jessica Stein, screenwriter, Heather Juergensen]
Generated description
Heather Juergensen is an American actress and writer best known for co-writing and starring in the indie romantic comedy film "Kissing Jessica Stein."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Heather Juergensen Target entity description: Heather Juergensen is an American actress and writer best known for co-writing and starring in the indie romantic comedy film "Kissing Jessica Stein."
-
A.
Lisa Gottsegen
Lisa Gottsegen is an American businesswoman and philanthropist best known as the longtime wife of actor Dustin Hoffman.
-
B.
Kimberly Schlapman
Kimberly Schlapman is an American country singer best known as a founding member and vocalist of the Grammy-winning group Little Big Town.
-
C.
Heather Faulkiner
Heather Faulkiner is known as the wife of prominent American sportscaster Marv Albert.
-
D.
Heather Persons
Heather Persons is a film editor best known for her work on the independent comedy-drama "Sunshine Cleaning."
-
E.
Denise Huth
Denise Huth is a television producer best known for her long-running work as an executive producer on AMC’s The Walking Dead franchise and its related spin-offs.
- 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_69d82790a7e08190877e2d349b2e8d8e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8f52ca7881908704eef20228aed3 |
completed | April 14, 2026, 7:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0170d8c9f0819099a398814f49f0ed |
completed | May 11, 2026, 6:02 a.m. |
| NEDg | Description generation | batch_6a017278b9408190ba496f554e55f833 |
completed | May 11, 2026, 6:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01732467408190b78c32296e20b55f |
completed | May 11, 2026, 6:11 a.m. |
Created at: April 10, 2026, 1:15 a.m.