Triple
T14582001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McAdory High School |
E342214
|
entity |
| Predicate | hasNotableSportAlumnus |
P114946
|
FINISHED |
| Object | George Pickens |
E586747
|
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: George Pickens | Statement: [McAdory High School, hasNotableSportAlumnus, George Pickens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: George Pickens Context triple: [McAdory High School, hasNotableSportAlumnus, George Pickens]
-
A.
George Pickens
chosen
George Pickens is an American football wide receiver in the NFL, known for his acrobatic catches and big-play ability.
-
B.
Allen George
Allen George is a writer best known for his work on the film "Fade."
-
C.
Sam Bromell
Sam Bromell is a screenwriter best known for co-writing Baz Luhrmann’s 2022 biographical musical film "Elvis."
-
D.
Joshua Norman
Joshua Norman is a member of the Norman family, related to Australian Olympic sprinter Peter Norman.
-
E.
Trey Burton
Trey Burton is an American former NFL tight end best known for throwing the touchdown pass to Nick Foles on the famous "Philly Special" trick play in Super Bowl LII.
- 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_69d822ddc0f081909cd8163c7de298cd |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb41e71748190a1deacc819dd26d3 |
completed | April 14, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda9167b888190abb8f301b0c7c55b |
completed | May 8, 2026, 9:12 a.m. |
Created at: April 10, 2026, 1:24 a.m.