Triple
T8317041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hangsaman |
E194730
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Natalie Waite |
E731742
|
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: Natalie Waite | Statement: [Hangsaman, mainCharacter, Natalie Waite]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Natalie Waite Context triple: [Hangsaman, mainCharacter, Natalie Waite]
-
A.
Natalie Waite
chosen
Natalie Waite is the introspective and psychologically troubled young woman who serves as the protagonist of Shirley Jackson’s novel "Hangsaman."
-
B.
Natalie Kingston
Natalie Kingston was an American film actress of the silent and early sound era, known for her roles in dramas and adventure films of the late 1920s.
-
C.
Faye Medwick
Faye Medwick is a fictional character appearing in the work titled "Chapter Two."
-
D.
Natalie Evans
Natalie Evans was the wife of Pulitzer Prize–winning American editorial cartoonist Bill Mauldin.
-
E.
Emily Charlton
Emily Charlton is the ambitious, fashion-obsessed first assistant to Miranda Priestly in "The Devil Wears Prada," known for her sharp wit and cutting remarks.
- 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_69ca82e6e2648190a31eaf6f4f757b2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f557a7881908adcf353f7297848 |
completed | March 31, 2026, 8:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce1ce5a0c881909ee517678cdc4ef2 |
completed | April 2, 2026, 7:38 a.m. |
Created at: March 30, 2026, 5:55 p.m.