Triple
T10357779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norman Black |
E244046
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Norman Black |
E244046
|
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: Norman Black | Statement: [Norman Black, name, Norman Black]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norman Black Context triple: [Norman Black, name, Norman Black]
-
A.
Norman Black
chosen
Norman Black is a former American professional basketball player and highly successful coach, best known for his long and decorated career in the Philippine Basketball Association.
-
B.
Norman Frank
Norman Frank is a member of the Frank family, known primarily as a relative of German author and Nazi critic Niklas Frank.
-
C.
Norman Milburn
Norman Milburn is a member of the Milburn family associated with famed English footballer Jackie Milburn.
-
D.
Norman Riley
Norman Riley is a distinguished mathematician and fluid dynamicist recognized for his influential contributions to theoretical and applied fluid mechanics.
-
E.
Norman Matson
Norman Matson was an American writer and screenwriter best known for co-writing the story that inspired the classic 1942 fantasy-comedy film "I Married a Witch."
- 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9563ea48190b8702b3ef497ed9a |
completed | April 7, 2026, 11:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8dc10284c8190bcce0f058b88ef0e |
completed | April 10, 2026, 11:16 a.m. |
Created at: April 6, 2026, 11:58 a.m.