Triple
T13475880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canada Lee |
E318249
|
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: [Canada Lee, givenName, Leonard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leonard Context triple: [Canada Lee, 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 one of the central characters in Mike Leigh’s play and film "Abigail’s Party," typically portrayed as a tense, status-conscious suburban husband.
-
D.
Laurence
Laurence is a masculine given name of Latin origin, commonly used in English-speaking countries.
-
E.
Léonard
Léonard is a given name and surname used in French-speaking contexts, corresponding to the name Leonhard or Leonard.
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf2551b48190a074fd256791742d |
completed | April 12, 2026, 2:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7462f94988190a857fa8cd32cdd0a |
completed | May 3, 2026, 12:57 p.m. |
Created at: April 9, 2026, 9:42 p.m.