Triple
T16580011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susan Walker |
E402804
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Sarah Alexander |
E186451
|
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: Sarah Alexander | Statement: [Susan Walker, portrayedBy, Sarah Alexander]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarah Alexander Context triple: [Susan Walker, portrayedBy, Sarah Alexander]
-
A.
Sarah Alexander
chosen
Sarah Alexander is a British actress best known for her roles in television comedies such as "Coupling" and "Green Wing."
-
B.
Christine Thayer
Christine Thayer is a central character in the film "Crash," depicted as a successful Black woman whose experiences expose racial tensions and injustices in contemporary Los Angeles.
-
C.
Jocelyn Harris
Jocelyn Harris is a fictional character portrayed by actress Alona Tal, best known from her role in the television series "Veronica Mars."
-
D.
Linda Howard
Linda Howard is a fictional protagonist featured in the film "Lost in America."
-
E.
Lucinda McCullough
Lucinda McCullough was the wife of renowned American bridge engineer Conde McCullough, associated with his personal and family life during his career in Oregon.
- 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_69d88387363c8190a97a0c942130de97 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35960834c819080eed0c9f32b881d |
completed | April 18, 2026, 10:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d449f708819095f83682fa03e3bf |
completed | May 10, 2026, 6:54 p.m. |
Created at: April 10, 2026, 5:16 a.m.