Triple
T19205790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bloomfield High School |
E480227
|
entity |
| Predicate | notableAlumnus |
P304
|
FINISHED |
| Object | Tom Fleming |
—
|
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: Tom Fleming | Statement: [Bloomfield High School, notableAlumnus, Tom Fleming]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Fleming Context triple: [Bloomfield High School, notableAlumnus, Tom Fleming]
-
A.
Tom Fleming
chosen
Tom Fleming is a name shared by several notable individuals, including an American long-distance runner and a Scottish actor and comedian.
-
B.
Michael Fleming
Michael Fleming is a British author best known for writing the official biography of his uncle, James Bond creator Ian Fleming.
-
C.
Brian Fleming
Brian Fleming is a personal name shared by several individuals, most commonly associated with professionals in fields such as law, politics, and the arts.
-
D.
John Clancy
John Clancy is a theatre orchestrator best known for his work on the Broadway musical adaptation of "Mean Girls."
-
E.
John Clancy
John Clancy is a leading architect and key figure at the prominent Irish architectural firm Scott Tallon Walker Architects.
- 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_69e5f99cc39c81909499b8d0b78b4665 |
completed | April 20, 2026, 10:02 a.m. |
Created at: April 10, 2026, 1:19 p.m.