Triple
T4589196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Sebastian |
E103440
|
entity |
| Predicate | LatinName |
P3646
|
FINISHED |
| Object | Sebastianus |
E57255
|
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: Sebastianus | Statement: [Saint Sebastian, LatinName, Sebastianus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sebastianus Context triple: [Saint Sebastian, LatinName, Sebastianus]
-
A.
Sebastiano
Sebastiano is an Italian given name, commonly used as the Italian form of Sebastian.
-
B.
Sebastian
chosen
Sebastian is a masculine given name of Latin origin, commonly used in many European and English-speaking countries.
-
C.
Livias
Livias was an ancient town in the region of Perea, east of the Jordan River, known from classical and biblical-era sources.
-
D.
Celso
Celso is a small village in southern Italy that serves as a frazione (hamlet) of the municipality of Pollica in the Campania region.
-
E.
Marinus
Marinus is a masculine given name of Latin origin historically associated with figures such as American Revolutionary War officer Marinus Willett.
- 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_69bd43dccaf08190aa89e9991a289719 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd592232888190af33c47636ca835d |
completed | March 20, 2026, 2:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bde0b9f700819082b0e5171132d0f3 |
completed | March 21, 2026, 12:05 a.m. |
Created at: March 20, 2026, 1:11 p.m.