Triple
T381805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lionel Logue |
E8696
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Lionel Logue |
E8696
|
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: Lionel Logue | Statement: [Lionel Logue, name, Lionel Logue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lionel Logue Context triple: [Lionel Logue, name, Lionel Logue]
-
A.
Lionel Logue
chosen
Lionel Logue was an Australian speech therapist best known for helping King George VI overcome his stammer, as depicted in the film "The King’s Speech."
-
B.
Gordon Holmes
Gordon Holmes is a name shared by several notable individuals, including a British neurologist and a mystery writer, recognized in their respective fields.
-
C.
Reginald Warneford
Reginald Warneford was a British World War I aviator and Victoria Cross recipient renowned for being the first pilot to destroy a German Zeppelin in mid-air.
-
D.
Richard Nurse
Richard Nurse is a Canadian former professional ice hockey player who competed in the World Hockey Association during the 1970s.
-
E.
John Edison Sweet
John Edison Sweet was an American mechanical engineer and inventor best known as a pioneering figure in the profession and an early leader in establishing standards and organization within the field.
- 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec2e3d5c8190b358bd9fd6b16a14 |
completed | Feb. 28, 2026, 1:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3fe9418348190a1ffb3fd3e3f8048 |
completed | March 1, 2026, 8:53 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.