Triple
T56597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norman |
E1119
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Norm |
E1119
|
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: Norm | Statement: [Norman, hasVariant, Norm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norm Context triple: [Norman, hasVariant, Norm]
-
A.
Nice
Nice is a prominent Mediterranean coastal city on the French Riviera, known for its mild climate, beaches, and vibrant cultural life.
-
B.
NE
NE is the common abbreviation for the New England Revolution, a professional Major League Soccer club based in the Greater Boston area.
-
C.
Norman
chosen
Norman is a masculine given name of English origin that became widely used in the English-speaking world.
-
D.
NAM
NAM is the commonly used acronym for the National Academy of Medicine, a leading U.S. nonprofit institution that provides expert advice on health, medicine, and biomedical science.
-
E.
IN
IN is the two-letter ISO 3166-1 alpha-2 country code representing India in international standards and systems.
- 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_69a248adc5b48190aa8db9fb092fb28a |
completed | Feb. 28, 2026, 1:45 a.m. |
| NER | Named-entity recognition | batch_69a24b07f4a881909e32115e84da02a3 |
completed | Feb. 28, 2026, 1:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2554a9e70819099ab14df3da5e403 |
completed | Feb. 28, 2026, 2:39 a.m. |
Created at: Feb. 28, 2026, 1:50 a.m.