Triple
T13539307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sissy Rommely |
E323340
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Sissy |
E822363
|
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: Sissy | Statement: [Sissy Rommely, givenName, Sissy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sissy Context triple: [Sissy Rommely, givenName, Sissy]
-
A.
Sissy
chosen
Sissy is a fictional character from the horror film "The Grave," known for her involvement in the movie’s dark, suspenseful storyline.
-
B.
Sissy Jupe
Sissy Jupe is a compassionate, imaginative young girl in Charles Dickens's novel "Hard Times," whose warmth and emotional intelligence contrast sharply with the book’s rigid, utilitarian society.
-
C.
Prissy
Prissy is a young enslaved house servant in Margaret Mitchell’s novel "Gone with the Wind," known for her fearful demeanor and memorable lines in the story.
-
D.
Prissy
Prissy is a diminutive nickname for the given name Priscilla, often used as an affectionate or informal form.
-
E.
Betsy
Betsy is a key female character in the 1976 film "Taxi Driver," known as the idealistic campaign worker who becomes the object of Travis Bickle’s fixation.
- 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_69d8076776248190bdf0d4fa1f85a5fc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafd7ad9481908fe1d7ffcf8fab71 |
completed | April 12, 2026, 2:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75d9c04b881908a359df791b89b43 |
completed | May 3, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:45 p.m.