Triple
T13667991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prey |
E327671
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Susan Reinhardt |
E1125380
|
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: Susan Reinhardt | Statement: [Prey, character, Susan Reinhardt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Susan Reinhardt Context triple: [Prey, character, Susan Reinhardt]
-
A.
Susan Reinhardt
chosen
Susan Reinhardt is a central character in the British crime drama series "Prey," around whom the second series' storyline revolves.
-
B.
Susan Anspach
Susan Anspach was an American actress best known for her roles in influential 1970s films such as "Five Easy Pieces" and "Blume in Love," where she often portrayed complex, independent women.
-
C.
Susan Hendler
Susan Hendler is a fictional character played by actress Caroline Goodall, likely appearing in a film or television production.
-
D.
Sarah E. Reisman
Sarah E. Reisman is an American organic chemist known for her work in complex natural product synthesis and as a professor at the California Institute of Technology.
-
E.
Susan Friedlander
Susan Friedlander is an American mathematician known for her contributions to fluid dynamics and partial differential equations, as well as for her leadership roles in the mathematical community.
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc65832688190aea688fee0a7cbdb |
completed | April 12, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe729a48288190bf24503af6522677 |
completed | May 8, 2026, 11:32 p.m. |
Created at: April 9, 2026, 9:52 p.m.