Triple
T3126867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff Bhasker |
E65317
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jeff |
E162857
|
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: Jeff | Statement: [Jeff Bhasker, givenName, Jeff]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeff Context triple: [Jeff Bhasker, givenName, Jeff]
-
A.
Jeff
chosen
Jeff is a masculine given name commonly used in English-speaking countries, often as a short form of Jeffrey or Jefferson.
-
B.
Jay
Jay is a small town located in Santa Rosa County in the northwestern part of Florida.
-
C.
Jay
Jay is the given first name of J. B. Pritzker, the American businessman, philanthropist, and governor of Illinois.
-
D.
Jay
Jay is the surname of John Jay, a prominent American Founding Father and the first Chief Justice of the United States.
-
E.
Jay
Jay is a former American football placekicker and current sports commentator best known for his long NFL career and broadcasting work.
- 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_69ad8580c72481909672d37acf647893 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada544cb648190b5ed430dbd561d52 |
completed | March 8, 2026, 4:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f7926248190b8f08e3a626e8eab |
completed | March 12, 2026, 12:57 a.m. |
Created at: March 8, 2026, 3:04 p.m.