Triple
T19065981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forks High School |
E466659
|
entity |
| Predicate | hasFictionalStudent |
P48
|
FINISHED |
| Object | Angela Weber |
—
|
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: Angela Weber | Statement: [Forks High School, hasFictionalStudent, Angela Weber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Angela Weber Context triple: [Forks High School, hasFictionalStudent, Angela Weber]
-
A.
Angela Weber
chosen
Angela Weber is a kind, soft-spoken classmate of Bella Swan in the Twilight series, known for her quiet loyalty and supportive nature.
-
B.
Angela Reide
Angela Reide is the central protagonist of "The Division," around whom the story’s key events and character dynamics revolve.
-
C.
Angela Abar
Angela Abar is the masked vigilante Sister Night and central protagonist of the HBO series "Watchmen," navigating themes of race, trauma, and legacy in an alternate-history America.
-
D.
Angela Martin
Angela Martin is a tightly wound, judgmental, and cat-obsessed accountant on the U.S. version of *The Office*, known for her strict moralism and tumultuous office romances.
-
E.
Angela Winkler
Angela Winkler is a German actress acclaimed for her powerful performances in film, television, and theater since the 1970s.
- 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e198621481908618f65dd01746fc |
completed | April 20, 2026, 8:19 a.m. |
Created at: April 10, 2026, 12:03 p.m.