Triple
T29454568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Replacements (2000 film) |
E747062
|
entity |
| Predicate | cheerleaderCharacter |
P12208
|
FINISHED |
| Object | Annabelle Farrell |
—
|
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: Annabelle Farrell | Statement: [The Replacements (2000 film), cheerleaderCharacter, Annabelle Farrell]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cheerleaderCharacter Context triple: [The Replacements (2000 film), cheerleaderCharacter, Annabelle Farrell]
-
A.
isCheerleader
Indicates that an entity performs the role or activity of being a cheerleader, typically leading or participating in organized cheering or support.
-
B.
hasCheerleaders
Indicates that an entity is associated with or supported by one or more cheerleaders.
-
C.
officialCheerleadersFor
Indicates that one entity serves as the formally recognized cheerleading squad or group supporting another entity, such as a team or organization.
-
D.
characterIn
chosen
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
E.
studentCharacter
Indicates that one entity has the role or qualities of a student in relation to another entity, typically within an educational or learning context.
- F. None of above.
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_69f0a7a230488190b44a97fe3d16f731 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f66b6b17c48190899f49d33946738e |
completed | May 2, 2026, 9:23 p.m. |
| PD | Predicate disambiguation | batch_69f66339175c819080bd70f0ff7057b1 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 3:35 p.m.