Triple
T11745599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Enna |
E279271
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object | Enna |
E61423
|
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: Enna | Statement: [Province of Enna, seat, Enna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Enna Context triple: [Province of Enna, seat, Enna]
-
A.
Enna
chosen
Enna is a historic hilltop city in central Sicily, Italy, known for its elevated position and panoramic views over the island.
-
B.
Ennia
Ennia was a former Dutch insurance company that later became part of Aegon through a merger.
-
C.
Ennia
Ennia is a historical figure known as the founder of the ancient city of Aegon.
-
D.
Nocciano
Nocciano is a small Italian town and comune in the Abruzzo region, known for its historic hilltop setting and traditional rural character.
-
E.
Sesto
Sesto is a central operatic character in Handel’s “Giulio Cesare,” portrayed as a young Roman seeking to avenge his father’s death.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4f2a38c8190a682d8dae1ab9415 |
completed | April 10, 2026, 7:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f0902f8c448190a71512353788ef09 |
completed | April 28, 2026, 10:47 a.m. |
Created at: April 8, 2026, 9:41 p.m.