Triple
T18933129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Doback |
E463165
|
entity |
| Predicate | hasLastName |
P18
|
FINISHED |
| Object | Doback |
—
|
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: Doback | Statement: [Robert Doback, hasLastName, Doback]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Doback Context triple: [Robert Doback, hasLastName, Doback]
-
A.
Doback
chosen
Doback is the surname of Dr. Robert Doback, a character from the comedy film "Step Brothers."
-
B.
Dobkin
Dobkin is a Jewish surname borne by various notable individuals, including figures in Israeli politics, arts, and public life.
-
C.
Doberdob
Doberdob is the Slovene name for Doberdò del Lago, a municipality in the Friuli Venezia Giulia region of northeastern Italy near the border with Slovenia.
-
D.
Dubiecko
Dubiecko is a small historic town in southeastern Poland, known as the birthplace of Enlightenment-era poet and bishop Ignacy Krasicki.
-
E.
Dobrush
Dobrush is a town in southeastern Belarus known for its paper industry and location near the Russian border in the Gomel Region.
- 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_69d8dcfec90481909e926be9767e5779 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d3e498308190bd1594cca841199c |
completed | April 20, 2026, 7:21 a.m. |
Created at: April 10, 2026, 11:59 a.m.