Triple
T16839147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kenneth Jay Lane |
E409359
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Lane |
E7099
|
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: Lane | Statement: [Kenneth Jay Lane, familyName, Lane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lane Context triple: [Kenneth Jay Lane, familyName, Lane]
-
A.
Lane
chosen
Lane is a common English surname borne by numerous notable individuals across fields such as science, politics, and the arts.
-
B.
Engineer Lane
Engineer Lane is a small street in Gibraltar’s town center, known for connecting to the main commercial thoroughfares and forming part of the territory’s dense urban street network.
-
C.
Jesus Lane
Jesus Lane is a historic street in central Cambridge, England, known for its proximity to several colleges and notable university buildings.
-
D.
Gillen Lane
Gillen Lane is the fictional protagonist of the apocalyptic thriller film "The Omega Code," portrayed as a brilliant biblical prophecy scholar drawn into a global conspiracy.
-
E.
Leota Lane
Leota Lane was an American actress and singer, best known as one of the performing Lane sisters who appeared in films and on radio in the 1930s and 1940s.
- 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_69d883952b048190887740a980b712ed |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b34f902c8190a334ba7caa04ce7e |
completed | April 18, 2026, 4:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00bb177e288190b525e6d239892d26 |
completed | May 10, 2026, 5:06 p.m. |
Created at: April 10, 2026, 5:23 a.m.