Triple
T15296585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian Van Dyke |
E365675
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Van Dyke |
E572375
|
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: Van Dyke | Statement: [Christian Van Dyke, familyName, Van Dyke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Van Dyke Context triple: [Christian Van Dyke, familyName, Van Dyke]
-
A.
Van Dyke
chosen
Van Dyke is a surname of Dutch origin borne by various notable individuals in fields such as science, the arts, and entertainment.
-
B.
Van Dyke
Van Dyke is the distinctive given name of American composer, arranger, and songwriter Van Dyke Parks, noted for his influential work in pop and experimental music.
-
C.
Benjamin Pond
Benjamin Pond was an early 19th-century American politician who served as a U.S. Representative from New York.
-
D.
Melancton
Melancton is a masculine given name most notably borne by Melancton Smith, an American lawyer and prominent Anti-Federalist politician of the late 18th century.
-
E.
Sewallis Shirley
Sewallis Shirley was a 19th-century British dog fancier and organizer best known for establishing The Kennel Club, the world’s first national kennel club for dog breeding and shows.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e036848c1881908fbaaae0216d6d27 |
completed | April 16, 2026, 1:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef81058c8190aec7c7ad9a68f569 |
completed | May 9, 2026, 8:25 a.m. |
Created at: April 10, 2026, 3:15 a.m.