Triple
T6697899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Snead |
E152797
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Les Snead |
E152797
|
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: Les Snead | Statement: [Les Snead, name, Les Snead]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Les Snead Context triple: [Les Snead, name, Les Snead]
-
A.
Les Snead
chosen
Les Snead is an American football executive best known for building the Los Angeles Rams’ Super Bowl–winning roster through bold trades and aggressive roster moves.
-
B.
Paul Snodgrass
Paul Snodgrass is a South African comedian, radio personality, and writer known for his stand-up performances and work in local media.
-
C.
Neil Snodgrass
Neil Snodgrass is an individual notable enough to be specifically cited as a bearer of the Snodgrass surname, though widely known public details about his life or achievements are limited.
-
D.
Michael Snodgrass
Michael Snodgrass is a person notable enough to be recognized as a bearer of the surname Snodgrass.
-
E.
Alan Snodgrass
Alan Snodgrass is an individual notable enough to be specifically cited as a bearer of the surname Snodgrass, though widely recognized public information about him is limited.
- 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_69c68807adbc8190b8632df42b39eda0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d0a4da9881908d79c410b4cff868 |
completed | March 27, 2026, 6:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6f7bd965881908a128d97f1c94dd0 |
completed | March 27, 2026, 9:33 p.m. |
Created at: March 27, 2026, 2:05 p.m.