Triple
T21990916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cecelia Halpert |
E543083
|
entity |
| Predicate | grandparent |
P2400
|
FINISHED |
| Object | Helene Beesly |
—
|
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: Helene Beesly | Statement: [Cecelia Halpert, grandparent, Helene Beesly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helene Beesly Context triple: [Cecelia Halpert, grandparent, Helene Beesly]
-
A.
Pam Beesly
chosen
Pam Beesly is a shy but witty receptionist-turned-office administrator and aspiring artist, best known as one of the central characters on the U.S. version of The Office.
-
B.
Mose Schrute
Mose Schrute is a socially awkward, eccentric beet farmer and Dwight Schrute’s cousin who lives and works at Schrute Farms in the U.S. version of The Office.
-
C.
Philip Schrute
Philip Schrute is the infant son of Dwight Schrute in the television series "The Office."
-
D.
Carole Bradshaw
Carole Bradshaw is a fictional character in the Top Gun film series, known as the mother of Bradley "Rooster" Bradshaw and the widow of Nick "Goose" Bradshaw.
-
E.
Peggy Olson
Peggy Olson is a central character in the television series "Mad Men," known for her rise from secretary to pioneering female copywriter in the 1960s advertising world.
- 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.