Triple
T2214921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lionel Logue |
E48007
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Lionel |
E48007
|
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 | Statement: [Lionel Logue, givenName, Lionel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lionel Context triple: [Lionel Logue, givenName, Lionel]
-
A.
Lionel
chosen
Lionel is the given name of Lionel Logue, the Australian speech therapist renowned for helping King George VI overcome his stammer.
-
B.
Leo the Lion
Leo the Lion is the iconic roaring lion featured in the opening logo of Metro-Goldwyn-Mayer (MGM) films.
-
C.
Percy the Lion
Percy the Lion is the official lion mascot of Newcastle University, symbolizing the institution’s spirit and identity at events and activities.
-
D.
Nigel
Nigel is a masculine given name of English origin, historically derived from the Latin name Nigellus and commonly used in the UK and other English-speaking countries.
-
E.
Milner
Milner is an English surname borne by various notable figures in politics, academia, and the arts.
- 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbff11574819091d1b50d637ae767 |
completed | March 7, 2026, 6:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae6554f3308190a180cac3ad7e2ce4 |
completed | March 9, 2026, 6:14 a.m. |
Created at: March 4, 2026, 7:46 p.m.