Triple
T15961632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barb Henrickson |
E387074
|
entity |
| Predicate | hasCoWife |
P59289
|
FINISHED |
| Object | Margene Heffman |
E322939
|
NE FINISHED |
How this triple was built (2 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: Margene Heffman | Statement: [Barb Henrickson, hasCoWife, Margene Heffman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Margene Heffman Context triple: [Barb Henrickson, hasCoWife, Margene Heffman]
-
A.
Margene Heffman
chosen
Margene Heffman is a fictional character from the television drama series "Big Love," known as the youngest and most free-spirited wife in a modern polygamist family.
-
B.
Melissa Winogrand
Melissa Winogrand is known as one of the children of influential American street photographer Garry Winogrand.
-
C.
Willa Hoffman
Willa Hoffman is the daughter of costume designer and director Mimi O'Donnell and the late actor Philip Seymour Hoffman.
-
D.
Marcella Niehoff
Marcella Niehoff was a pioneering American nurse and educator whose legacy in advancing nursing education is commemorated by the nursing school that bears her name.
-
E.
Susan Duerden
Susan Duerden is a British actress known for her voice and screen roles in film, television, and audio productions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1828cd83c8190a3e15cccc8342c1f |
completed | April 17, 2026, 12:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffcf16b1b881909768d18b889260da |
completed | May 10, 2026, 12:19 a.m. |
Created at: April 10, 2026, 4:53 a.m.