Triple
T21991060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pete Halpert |
E543087
|
entity |
| Predicate | hasFictionalRelative |
P7844
|
FINISHED |
| Object | Betsy Halpert |
—
|
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: Betsy Halpert | Statement: [Pete Halpert, hasFictionalRelative, Betsy Halpert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Betsy Halpert Context triple: [Pete Halpert, hasFictionalRelative, Betsy Halpert]
-
A.
Betsy Halpert
chosen
Betsy Halpert is a member of the Halpert family, known in popular culture as part of the extended family of Jim and Pam from the television series "The Office."
-
B.
Pam Halpert
Pam Halpert is a fictional receptionist-turned-office administrator and aspiring artist from the U.S. television series "The Office."
-
C.
Betsy Sodaro
Betsy Sodaro is an American comedian and character actress known for her high-energy performances in television comedies and improv.
-
D.
Maureen Blumhardt
Maureen Blumhardt is a former model and legal aide best known as the longtime wife of NBA Hall of Famer Charles Barkley.
-
E.
Marla Frumkin
Marla Frumkin is an American voice actress best known for portraying Velma Dinkley in the Scooby-Doo animated franchise.
- 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_69e0c48136b081908831fa907cc02e18 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1270d7cbc819086eea86be04a2ec0 |
completed | April 28, 2026, 9:30 p.m. |
Created at: April 16, 2026, 8:05 p.m.