Triple
T18475957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neil Snodgrass |
E451432
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Snodgrass |
—
|
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: Snodgrass | Statement: [Neil Snodgrass, hasSurname, Snodgrass]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Snodgrass Context triple: [Neil Snodgrass, hasSurname, Snodgrass]
-
A.
Snodgrass
chosen
Snodgrass is a surname of English and Scottish origin borne by various notable individuals in sports, politics, and the arts.
-
B.
Scoggins
Scoggins is a minor supporting character in the 1999 science fiction horror film "Deep Blue Sea," which centers on genetically enhanced sharks in an underwater research facility.
-
C.
Peatross
Peatross is a surname most notably associated with Oscar F. Peatross, a distinguished United States Marine Corps officer.
-
D.
Scarphe
Scarphe is a figure from Greek mythology known primarily as the wife of Aeson, the father of the hero Jason.
-
E.
Trulaske
Trulaske is the commonly used name for the Robert J. Trulaske, Sr. College of Business at the University of Missouri, a business school offering undergraduate and graduate programs in fields such as accounting, finance, and management.
- 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_69d8d38465a0819099b9b42d2a662ac1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53062f67881909620c4e8fc00eb7d |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 11:34 a.m.