Triple
T12037164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sabines |
E286570
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Sabinum |
E225367
|
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: Sabinum | Statement: [Sabines, region, Sabinum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sabinum Context triple: [Sabines, region, Sabinum]
-
A.
Sabinum
chosen
Sabinum was the ancient central Italian region traditionally associated with the Sabine people, located in the Apennine area northeast of Rome.
-
B.
Saepinum
Saepinum was an ancient town of the Samnite people in south-central Italy, later developed into a Roman municipium whose ruins are still visible today.
-
C.
Statilia
Statilia is an ancient Roman feminine praenomen (given name) most notably borne by the empress Statilia Messalina, wife of Emperor Nero.
-
D.
Decumano
Decumano was the central pedestrian boulevard of Expo 2015 in Milan, along which the majority of national pavilions and exhibition spaces were arranged.
-
E.
Maenza
Maenza is a small historic town in the Lazio region of central Italy, known for its medieval architecture and hilltop setting.
- 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9040a8be881908f4841145a7b4e86 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49d8a9af881909e28783b0d83ed82 |
completed | May 1, 2026, 12:33 p.m. |
Created at: April 8, 2026, 9:47 p.m.