Triple
T17714014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amy Franklin |
E442141
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Linda Hamilton |
—
|
NE NERFINISHED |
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: Linda Hamilton | Statement: [Amy Franklin, portrayedBy, Linda Hamilton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linda Hamilton Context triple: [Amy Franklin, portrayedBy, Linda Hamilton]
-
A.
Linda Hamilton
chosen
Linda Hamilton is an American actress best known for her iconic role as Sarah Connor in the "Terminator" film series.
-
B.
Tawny Kitaen
Tawny Kitaen was an American actress and model best known for her appearances in 1980s rock music videos, particularly for the band Whitesnake.
-
C.
Lea Thompson
Lea Thompson is an American actress best known for her role as Lorraine Baines McFly in the Back to the Future film trilogy.
-
D.
Alexandra Hedison
Alexandra Hedison is an American photographer, director, and former actress known for her contemporary art photography and her work on the television series "The L Word."
-
E.
Lynne Brimley
Lynne Brimley is best known as the wife of American character actor Wilford Brimley.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4729cebd08190872be96a26d0f7ce |
completed | April 19, 2026, 6:13 a.m. |
Created at: April 10, 2026, 10:06 a.m.