Triple
T22656528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernard Freeman |
E559240
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Freeman |
—
|
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: Freeman | Statement: [Bernard Freeman, familyName, Freeman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Freeman Context triple: [Bernard Freeman, familyName, Freeman]
-
A.
Freeman
Freeman is the individual after whom the Freeman Scholar Award is named, recognized for significant contributions in their field that inspired the creation of this honor.
-
B.
Freeman
chosen
Freeman is a common English surname borne by numerous notable individuals, including acclaimed American actor and narrator Morgan Freeman.
-
C.
Freeman
Freeman Dyson was a renowned theoretical physicist and mathematician known for his work in quantum electrodynamics, solid-state physics, and futurist writings.
-
D.
Freeman
Freeman is a historical novel by Leonard Pitts Jr. that explores the struggles and hopes of formerly enslaved people in the aftermath of the American Civil War.
-
E.
Freeman Meskimen
Freeman Meskimen was an American actor and the husband of actress Marion Ross.
- 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_69e245489dd88190b1f674acf61c8769 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1765c62bc8190b3fcde76d6b6dfb6 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 3:06 p.m.