Triple
T19358987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hart to Hart |
E484225
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Jennifer Hart
Jennifer Hart is a glamorous, intelligent, and adventurous wealthy socialite and amateur sleuth from the television series "Hart to Hart."
|
E1371689
|
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 Hart | Statement: [Hart to Hart, character, Jennifer Hart]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jennifer Hart Context triple: [Hart to Hart, character, Jennifer Hart]
-
A.
Laura Harring
Laura Harring is a Mexican-American actress best known for her acclaimed role in David Lynch's film "Mulholland Drive."
-
B.
Jennifer Heath
Jennifer Heath is a screenwriter best known for co-writing the film adaptation of the fantasy novel "Ella Enchanted."
-
C.
Jennifer Kirk
Jennifer Kirk is an American former competitive figure skater who won the 2000 Four Continents Championships and later became known for her commentary and advocacy on issues within the sport.
-
D.
Lisa Harrow
Lisa Harrow is a New Zealand-born actress known for her work in film, television, and theatre, including prominent roles in Australian and British productions.
-
E.
Laura Davenport
Laura Davenport is the daughter of English actor Nigel Davenport.
- 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 Hart Triple: [Hart to Hart, character, Jennifer Hart]
Generated description
Jennifer Hart is a glamorous, intelligent, and adventurous wealthy socialite and amateur sleuth from the television series "Hart to Hart."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jennifer Hart Target entity description: Jennifer Hart is a glamorous, intelligent, and adventurous wealthy socialite and amateur sleuth from the television series "Hart to Hart."
-
A.
Laura Harring
Laura Harring is a Mexican-American actress best known for her acclaimed role in David Lynch's film "Mulholland Drive."
-
B.
Jennifer Heath
Jennifer Heath is a screenwriter best known for co-writing the film adaptation of the fantasy novel "Ella Enchanted."
-
C.
Jennifer Kirk
Jennifer Kirk is an American former competitive figure skater who won the 2000 Four Continents Championships and later became known for her commentary and advocacy on issues within the sport.
-
D.
Lisa Harrow
Lisa Harrow is a New Zealand-born actress known for her work in film, television, and theatre, including prominent roles in Australian and British productions.
-
E.
Laura Davenport
Laura Davenport is the daughter of English actor Nigel Davenport.
- 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_69d8e8d305088190ad13571532aa454c |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e6190b343c81909734ba776fd196dc |
completed | April 20, 2026, 12:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07240dacb881909a8acdb5dab42115 |
completed | May 15, 2026, 1:47 p.m. |
| NEDg | Description generation | batch_6a07253d53488190a25b4c65c93e70d7 |
completed | May 15, 2026, 1:53 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a072657035881909c63391b274063e1 |
completed | May 15, 2026, 1:57 p.m. |
Created at: April 10, 2026, 1:34 p.m.