Triple
T3868422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rufus Blodgett |
E91916
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Blodgett |
E91916
|
NE FINISHED |
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: Blodgett | Statement: [Rufus Blodgett, hasSurname, Blodgett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blodgett Context triple: [Rufus Blodgett, hasSurname, Blodgett]
-
A.
Blodgett
chosen
Blodgett is a surname of English origin borne by various notable individuals across fields such as politics, business, and the arts.
-
B.
Danby
Danby is a small rural village in North Yorkshire, England, known for its scenic setting within the North York Moors National Park.
-
C.
Danby
Danby is a small rural town in Tompkins County, New York, known for its scenic landscapes and proximity to the city of Ithaca.
-
D.
Robart
Robart is an alternative spelling of the given name Robert, typically used as a personal or family name.
-
E.
Brinkman
Brinkman is a surname of Germanic origin borne by various notable individuals across fields such as sports, politics, and the arts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69aed9645f348190a9868e7cef56ab7e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec3dfb3c8190a0a07070f0d76bf6 |
completed | March 9, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b562821c3c81909805cb877288405b |
completed | March 14, 2026, 1:28 p.m. |
Created at: March 9, 2026, 3:20 p.m.