Triple
T27165274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wolf Pack |
E682764
|
entity |
| Predicate | Sarah Michelle GellarRole |
P9616
|
FINISHED |
| Object | Kristen Ramsey |
—
|
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: Kristen Ramsey | Statement: [Wolf Pack, Sarah Michelle GellarRole, Kristen Ramsey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Sarah Michelle GellarRole Context triple: [Wolf Pack, Sarah Michelle GellarRole, Kristen Ramsey]
-
A.
Kim CattrallRole
Indicates that Kim Cattrall played a specific role or character in a work such as a film, TV show, or stage production.
-
B.
creditedRoleOf
Indicates that a particular role or position is formally acknowledged as being held or performed by a specific entity in a credit or attribution context.
-
C.
playedBy
chosen
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
-
D.
MarilynMonroeRoleType
Indicates the type or category of role associated with Marilyn Monroe in a given context.
-
E.
leadActress
Indicates that the subject is the primary female performer in the specified film, show, or production.
- 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_69eefacf6e788190a75a64399d9e3109 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f62541e49c8190ae9f30f48a30f814 |
completed | May 2, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69f61b40f02081909bd9c3ea73249163 |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 9:20 a.m.