Triple
T562403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lionel Richie |
E13480
|
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 Richie, givenName, Lionel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lionel Context triple: [Lionel Richie, 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.
Cecil
Cecil is a masculine given name most famously associated with pioneering American film director and producer Cecil B. DeMille.
-
D.
Sylvester
Sylvester is a classic Looney Tunes cartoon cat best known for his lisping voice and comical attempts to catch Tweety Bird.
-
E.
Maurice
Maurice is a masculine given name of Latin origin, commonly used in English and French-speaking countries.
- 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49a700e608190b235246df057bd9b |
completed | March 1, 2026, 7:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5089bce6c8190a5c4f708fb94668b |
completed | March 2, 2026, 3:48 a.m. |
Created at: March 1, 2026, 7:32 p.m.