Triple
T9402676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ray Wood |
E226512
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ray Wood |
E226512
|
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: Ray Wood | Statement: [Ray Wood, name, Ray Wood]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ray Wood Context triple: [Ray Wood, name, Ray Wood]
-
A.
Ray Wood
chosen
Ray Wood was an English footballer for Manchester United who survived the 1958 Munich air disaster.
-
B.
Don Woods
Don Woods is an American computer programmer best known for co-creating and expanding the pioneering text adventure game Colossal Cave Adventure.
-
C.
Leon Barmore
Leon Barmore is a legendary women's college basketball coach best known for leading the Louisiana Tech Lady Techsters to national prominence and multiple NCAA championships.
-
D.
Milt Woodard
Milt Woodard was a sports executive best known for serving as commissioner of the American Football League during its final years before the AFL–NFL merger.
-
E.
Scott Norwood
Scott Norwood is a former NFL placekicker best known for his crucial missed field goal in Super Bowl XXV while playing for the Buffalo Bills.
- 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_69ca843170f88190800a8ab2b5fc568e |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd51be35cc8190bafad423a142c305 |
completed | April 1, 2026, 5:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1012ca6c0819098c427233d226dd2 |
completed | April 4, 2026, 12:16 p.m. |
Created at: March 30, 2026, 7:46 p.m.