Triple
T596023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freeman Dyson |
E17384
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Freeman |
E23818
|
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: Freeman | Statement: [Freeman Dyson, givenName, Freeman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Freeman Context triple: [Freeman Dyson, givenName, Freeman]
-
A.
Freeman
chosen
Freeman Dyson was a renowned theoretical physicist and mathematician known for his work in quantum electrodynamics, solid-state physics, and futurist writings.
-
B.
Hudson Fysh
Hudson Fysh was an Australian aviator and businessman best known as a co-founder and long-serving leader of Qantas, helping to establish it as a major international airline.
-
C.
Jeffrey
Jeffrey is a masculine given name of Germanic origin, commonly used in English-speaking countries.
-
D.
Lewis
"Lewis" is a notable film or television work featuring British actor Edward Fox, recognized as part of his distinguished acting career.
-
E.
Sam De Grasse
Sam De Grasse was a Canadian-born silent film actor best known for his villainous roles in early Hollywood adventure and drama films.
- 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_69a49379d09c8190ac7e00b24e2810b1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49bd3e5e08190be95cb2009aad42d |
completed | March 1, 2026, 8:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a518c61744819090ccc037d61a61b1 |
completed | March 2, 2026, 4:57 a.m. |
Created at: March 1, 2026, 7:33 p.m.