Triple
T12183898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BrainCraft |
E290284
|
entity |
| Predicate | host |
P2592
|
FINISHED |
| Object | Vanessa Hill |
E969768
|
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: Vanessa Hill | Statement: [BrainCraft, host, Vanessa Hill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vanessa Hill Context triple: [BrainCraft, host, Vanessa Hill]
-
A.
Vanessa Hill
chosen
Vanessa Hill is a science communicator and educator best known for creating the popular YouTube channel and PBS series BrainCraft, which explores psychology, neuroscience, and human behavior.
-
B.
Vanessa Brown
Vanessa Brown was an Austrian-born American actress known for her work in mid-20th-century Hollywood films, radio, and stage productions.
-
C.
Vanessa Howard
Vanessa Howard was a British actress known for her roles in 1960s and 1970s horror and exploitation films, including "The Blood Beast Terror" and "Mumsy, Nanny, Sonny & Girly."
-
D.
Vanessa Haywood
Vanessa Haywood is a South African actress and model best known for her role in the science fiction film "District 9."
-
E.
Vanessa Black
Vanessa Black is a chef and television personality known for her culinary work and for being married to dancer and chef Dean Sheremet.
- 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d915ffe644819085f4eb64802fe349 |
completed | April 10, 2026, 3:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e505fc481909cdd2dabcef8d948 |
completed | May 2, 2026, 3:54 p.m. |
Created at: April 8, 2026, 9:50 p.m.