Triple
T7870852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leonard Tose |
E182732
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Leonard |
E53541
|
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: Leonard | Statement: [Leonard Tose, givenName, Leonard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leonard Context triple: [Leonard Tose, givenName, Leonard]
-
A.
Leonard
chosen
Leonard is a masculine given name of Germanic origin, commonly used in English-speaking countries and borne by numerous notable figures in arts, sports, and public life.
-
B.
Leonard Skinner
Leonard Skinner was a high school gym teacher whose strict enforcement of hair-length rules famously inspired the name of the Southern rock band Lynyrd Skynyrd.
-
C.
Laurence
Laurence is a masculine given name of Latin origin, commonly used in English-speaking countries.
-
D.
Léonard
Léonard is a given name and surname used in French-speaking contexts, corresponding to the name Leonhard or Leonard.
-
E.
Leonard Graves
Leonard Graves was an American actor and voice artist best known for narrating the acclaimed World War II documentary television series "Victory at Sea."
- 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_69ca82894d9081908a832bfce71a4714 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb384a285881908a5b2de278f9556f |
completed | March 31, 2026, 2:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5b6bc7248190adbf4377c52e16a9 |
completed | March 31, 2026, 5:28 a.m. |
Created at: March 30, 2026, 4:55 p.m.