Triple
T7541647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aloysya |
E178289
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Aloysius |
E175595
|
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: Aloysius | Statement: [Aloysya, relatedName, Aloysius]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aloysius Context triple: [Aloysya, relatedName, Aloysius]
-
A.
Aloysius
chosen
Aloysius is a masculine given name of Latinized form, historically borne by several saints and used in various European languages.
-
B.
Ignazio
Ignazio is an Italian given name, cognate to Ignacy and typically associated with the Latin-rooted names Ignatius and Ignacio.
-
C.
Benedetto
Benedetto is the Italian form of the given name Benedict, traditionally associated with blessings and several notable religious and historical figures.
-
D.
Brother Theodore
Brother Theodore was a German-American monologist and actor known for his darkly comedic, existential rants and cult appearances on late-night television and in offbeat films.
-
E.
Gabriele
Gabriele is a feminine given name of Italian origin, commonly used in various European 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_69c69f2be3888190a6667a27f8f195e9 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8750f80819088ddfb7a5580b5df |
completed | March 27, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8614c958081908021a0341dc29725 |
completed | March 28, 2026, 11:16 p.m. |
Created at: March 27, 2026, 3:48 p.m.