Triple
T23362633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mose Schrute |
E593223
|
entity |
| Predicate | hasLastName |
P18
|
FINISHED |
| Object | Schrute |
—
|
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: Schrute | Statement: [Mose Schrute, hasLastName, Schrute]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schrute Context triple: [Mose Schrute, hasLastName, Schrute]
-
A.
Mose Schrute
chosen
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.
-
B.
Dwight Schrute
Dwight Schrute is an eccentric, intensely loyal and competitive paper salesman and beet farmer best known as the quirky assistant to the regional manager on 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.
Jim Halpert
Jim Halpert is a witty and laid-back salesman at Dunder Mifflin known for his pranks on Dwight and his romance with Pam in the U.S. version of The Office.
-
E.
Michael Scott Ryan
Michael Scott Ryan is a British author and academic best known as the husband of actress Jennifer Ehle.
- 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_69e25d2593c88190bcdf4a716a94ccb2 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a0aa0ed88190b0198cbfd1bcc59b |
completed | April 29, 2026, 6:09 a.m. |
Created at: April 17, 2026, 5:30 p.m.