Triple
T4066436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wellcome Trust |
E86334
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Henry Wellcome |
E410492
|
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: Henry Wellcome | Statement: [Wellcome Trust, namedAfter, Henry Wellcome]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Henry Wellcome Context triple: [Wellcome Trust, namedAfter, Henry Wellcome]
-
A.
Henry Wellcome
chosen
Henry Wellcome was a British-American pharmaceutical entrepreneur and philanthropist whose fortune and vision led to the creation of one of the world’s largest biomedical research charities.
-
B.
William Fryer Harvey
William Fryer Harvey was an English writer best known for his influential horror and supernatural short stories.
-
C.
Robert Hodgkin
Robert Hodgkin is a notable individual distinguished enough to be recognized as a prominent bearer of the Hodgkin surname.
-
D.
William Halstead
William Halstead was a 19th-century American politician who served multiple terms as a U.S. Representative from New Jersey.
-
E.
John Callcott Horsley
John Callcott Horsley was a 19th-century English painter and illustrator best known for designing the first commercially produced Christmas card.
- 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_69aed93c69208190a4efac0efe3cd69b |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefbf58d9c8190936e453b0d397cb0 |
completed | March 9, 2026, 4:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56b55b5388190a90551c43388f3fc |
completed | March 14, 2026, 2:06 p.m. |
Created at: March 9, 2026, 3:38 p.m.