Triple
T6233373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David H. Souter |
E139410
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Souter |
E139410
|
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: Souter | Statement: [David H. Souter, familyName, Souter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Souter Context triple: [David H. Souter, familyName, Souter]
-
A.
Souter
chosen
Souter is a surname most prominently associated with David H. Souter, a former Associate Justice of the United States Supreme Court.
-
B.
Calderbank
Calderbank is a small village in North Lanarkshire, Scotland, historically associated with coal mining and ironworks.
-
C.
Southery
Southery is a village and civil parish in Norfolk, England, situated in the Fens near the River Great Ouse.
-
D.
Sutherland
Sutherland is a sparsely populated historic county in the far north of mainland Scotland, known for its dramatic coastal scenery, mountains, and remote landscapes.
-
E.
Sutherland
Sutherland is a small town in the Northern Cape province of South Africa, best known for its exceptionally clear night skies and major astronomical observatories.
- 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_69c008b0e7ac8190808a59573ee646f3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062efa25c8190a54f5a6f5b5ad24f |
completed | March 22, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c243f785dc819084d2a11151d84227 |
completed | March 24, 2026, 7:57 a.m. |
Created at: March 22, 2026, 4:22 p.m.