Triple
T18706332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Eaton |
E457376
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | John |
—
|
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: John | Statement: [John Eaton, givenName, John]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Context triple: [John Eaton, givenName, John]
-
A.
John
John Vassall Jr. was a British civil servant who became notorious as a Soviet spy during the Cold War.
-
B.
John
John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
-
C.
John
John is the given name of John Albert William Spencer-Churchill, a British aristocrat and 10th Duke of Marlborough.
-
D.
John
John is the given name of John Cornford, a British poet and communist who was killed while fighting in the Spanish Civil War.
-
E.
John
John is the first name of Jack Graney, a Canadian Major League Baseball player and later a pioneering baseball broadcaster.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5671717b88190974f542015f641e8 |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 10, 2026, 11:50 a.m.