Triple
T8395478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scott Silver |
E198041
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Johns |
E179736
|
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: Johns | Statement: [Scott Silver, notableWork, Johns]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Johns Context triple: [Scott Silver, notableWork, Johns]
-
A.
Johns
chosen
Johns is a given name most notably associated with Johns Hopkins, the 19th-century American entrepreneur and philanthropist whose endowments founded Johns Hopkins University and Hospital.
-
B.
Jones
Jones is a common English-language surname borne by numerous notable individuals across fields such as entertainment, sports, politics, and science.
-
C.
The Johns
The Johns is the informal nickname of the Regina Rifle Regiment, an infantry unit of the Canadian Army Reserve.
-
D.
John
John is the given name of the late Canadian actor and comedian John Candy, known for his roles in films like "Planes, Trains and Automobiles" and "Uncle Buck."
-
E.
John
John is the given name of John Egerton, 2nd Duke of Bridgewater, an 18th-century English nobleman known for pioneering canal construction during the Industrial Revolution.
- 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_69ca82f816bc8190ab321c07d72208c1 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb81874d6c8190bbc0ac832d8a339d |
completed | March 31, 2026, 8:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cde85ee7b08190bfbcbed0edb142dd |
completed | April 2, 2026, 3:54 a.m. |
Created at: March 30, 2026, 6:04 p.m.