Triple
T1721165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asbury Francis Lever |
E37393
|
entity |
| Predicate | middleName |
P143
|
FINISHED |
| Object | Francis |
E14156
|
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: Francis | Statement: [Asbury Francis Lever, middleName, Francis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Francis Context triple: [Asbury Francis Lever, middleName, Francis]
-
A.
Francis
chosen
Francis is the papal name of the current head of the Roman Catholic Church, known for his emphasis on humility, social justice, and interfaith dialogue.
-
B.
Aloysius
Aloysius is a masculine given name of Latinized form, historically borne by several saints and used in various European languages.
-
C.
Francesco
Francesco is the birth name of Frank Capra, the renowned Italian-American film director known for classic Hollywood movies such as "It's a Wonderful Life."
-
D.
Benedict
Benedict is a masculine given name of Latin origin, most famously borne in modern times by the British actor Benedict Cumberbatch.
-
E.
Francisco
Francisco is a masculine given name of Spanish and Portuguese origin, equivalent to Francis in English.
- 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_69a8861912dc8190931af43b4b9158a7 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa63558d7c8190830cb8ee2e4a8932 |
completed | March 6, 2026, 5:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8aeca12881908efad5991bb0f12b |
completed | March 8, 2026, 2:42 p.m. |
Created at: March 4, 2026, 7:30 p.m.