Triple
T7213112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Louis of Toulouse |
E149458
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Louis |
E447876
|
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: Louis | Statement: [Saint Louis of Toulouse, givenName, Louis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Louis Context triple: [Saint Louis of Toulouse, givenName, Louis]
-
A.
Louis
Louis is the friendly, trumpet-playing alligator who dreams of becoming a jazz musician in Disney's animated film "The Princess and the Frog."
-
B.
Louis
Louis is the given name of Louis Armstrong, the legendary American jazz trumpeter and singer.
-
C.
Louis
Louis is the given name of Louis Sullivan, the influential American architect often called the “father of skyscrapers.”
-
D.
Louis
Louis is the family name of Spyridon Louis, the Greek runner who won the first modern Olympic marathon in 1896.
-
E.
Louis
chosen
Louis is the French form of the given name Luís, historically borne by numerous French kings and notable figures.
- 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_69c687eca814819095abb52316b1af80 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e98b61448190add3624a818fdc7b |
completed | March 27, 2026, 8:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7bfcec3448190ab29c3742aa167ae |
completed | March 28, 2026, 11:47 a.m. |
Created at: March 27, 2026, 2:53 p.m.