Triple
T4968296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faetar |
E111579
|
entity |
| Predicate | hasPhonologicalInfluenceFrom |
P4183
|
FINISHED |
| Object | Italian |
E3588
|
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: Italian | Statement: [Faetar, hasPhonologicalInfluenceFrom, Italian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Italian Context triple: [Faetar, hasPhonologicalInfluenceFrom, Italian]
-
A.
The Italian
The Italian is a 1797 Gothic novel by Ann Radcliffe, renowned for its suspenseful plot, atmospheric settings, and exploration of religious and psychological themes.
-
B.
Italian language
chosen
The Italian language is a Romance language spoken primarily in Italy and parts of Switzerland, known for its Latin roots, melodic sound, and central role in art, music, and culinary culture.
-
C.
Italo
Italo is a masculine Italian given name historically borne by notable figures in politics, aviation, literature, and the arts.
-
D.
Italo
Italo is a private Italian high-speed train operator known for connecting major cities across Italy with fast, modern rail services.
-
E.
Milanese
Milanese is a Western Lombard dialect spoken primarily in and around the city of Milan in northern Italy.
- 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_69bd441a0eb481908050fa4273b19eae |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7210c8f081908e36595a12d07f64 |
completed | March 20, 2026, 4:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be89fddbb8819084c8c21ee0ce845e |
completed | March 21, 2026, 12:07 p.m. |
Created at: March 20, 2026, 1:32 p.m.