Triple
T4707170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susan Lucci |
E104416
|
entity |
| Predicate | parentOf |
P120
|
FINISHED |
| Object |
Liza Huber
Liza Huber is an American actress best known for her role on the soap opera "Passions" and as the daughter of daytime television star Susan Lucci.
|
E488932
|
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: Liza Huber | Statement: [Susan Lucci, parentOf, Liza Huber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liza Huber Context triple: [Susan Lucci, parentOf, Liza Huber]
-
A.
Lila Hotz
Lila Hotz was the first wife of American magazine magnate Henry Luce, co-founder of Time Inc.
-
B.
Stephanie Huber
Stephanie Huber is a notable individual recognized as a bearer of the surname Huber.
-
C.
Lisa Eilbacher
Lisa Eilbacher is an American actress best known for her roles in 1980s films and television series, including prominent appearances in action and drama movies.
-
D.
Cynthia Ludwig
Cynthia Ludwig is a film editor known for her work on the 2009 horror film "My Bloody Valentine 3D."
-
E.
Lisa Bluder
Lisa Bluder is a longtime head coach of the University of Iowa women's basketball team, known for leading the Hawkeyes to national prominence behind star players like Caitlin Clark.
- 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: Liza Huber Triple: [Susan Lucci, parentOf, Liza Huber]
Generated description
Liza Huber is an American actress best known for her role on the soap opera "Passions" and as the daughter of daytime television star Susan Lucci.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Liza Huber Target entity description: Liza Huber is an American actress best known for her role on the soap opera "Passions" and as the daughter of daytime television star Susan Lucci.
-
A.
Lila Hotz
Lila Hotz was the first wife of American magazine magnate Henry Luce, co-founder of Time Inc.
-
B.
Stephanie Huber
Stephanie Huber is a notable individual recognized as a bearer of the surname Huber.
-
C.
Lisa Eilbacher
Lisa Eilbacher is an American actress best known for her roles in 1980s films and television series, including prominent appearances in action and drama movies.
-
D.
Cynthia Ludwig
Cynthia Ludwig is a film editor known for her work on the 2009 horror film "My Bloody Valentine 3D."
-
E.
Lisa Bluder
Lisa Bluder is a longtime head coach of the University of Iowa women's basketball team, known for leading the Hawkeyes to national prominence behind star players like Caitlin Clark.
- 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_69bd43eac3c08190af7e4020c6c3704c |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd63e9f0b88190820aa7fba2f91b6e |
completed | March 20, 2026, 3:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be9c3ab02081908b308880afbd8f5a |
completed | March 21, 2026, 1:25 p.m. |
| NEDg | Description generation | batch_69be9ec9c9ec8190a846c20bfbf44254 |
completed | March 21, 2026, 1:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69be9f243e408190a0dd90155b0667d4 |
completed | March 21, 2026, 1:37 p.m. |
Created at: March 20, 2026, 1:17 p.m.