Triple
T19215260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julius Schwartz |
E480464
|
entity |
| Predicate | notableCollaboration |
P8554
|
FINISHED |
| Object | John Broome |
—
|
NE NERFINISHED |
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: John Broome | Statement: [Julius Schwartz, notableCollaboration, John Broome]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Broome Context triple: [Julius Schwartz, notableCollaboration, John Broome]
-
A.
John Broome
John Broome is a British philosopher and economist known for his influential work on ethics, rationality, and climate change.
-
B.
John Broome
chosen
John Broome was an American comic book writer best known for his influential work at DC Comics, particularly on Green Lantern and The Flash during the Silver Age of comics.
-
C.
John Broome
John Broome was an American politician who served as Lieutenant Governor of New York in the early 19th century.
-
D.
Geoffrey Brock
Geoffrey Brock is an American poet and translator renowned for his acclaimed English translations of Italian literature.
-
E.
John Burrows
John Burrows is a fictional character featured in the 1951 British drama film "Journey into Light."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8cb8c348190b52075823911c869 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fa3a417c819083e2e276d44d4d89 |
completed | April 20, 2026, 10:04 a.m. |
Created at: April 10, 2026, 1:22 p.m.