Triple
T9442541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calabria |
E227681
|
entity |
| Predicate | mountainRange |
P648
|
FINISHED |
| Object | Sila |
E299329
|
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: Sila | Statement: [Calabria, mountainRange, Sila]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sila Context triple: [Calabria, mountainRange, Sila]
-
A.
Sila
chosen
Sila is a mountainous plateau in Calabria, southern Italy, known for its dense forests, lakes, and national park.
-
B.
Sihala
Sihala is a settlement in Pakistan located near the Soan River, known primarily for its proximity to this important waterway in the region.
-
C.
Silay
Silay is a heritage-rich city in the Philippine province of Negros Occidental, known for its well-preserved ancestral houses and cultural history.
-
D.
Trisaia
Trisaia is an ENEA research center site in southern Italy known for its activities in energy, environmental, and nuclear technology research.
-
E.
Tenea
Tenea was an ancient Greek city, traditionally associated with Corinthian colonists and mythic Trojan origins, known from classical sources and archaeological discoveries in the Peloponnese.
- 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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f300cc88190a793712706295c53 |
completed | April 1, 2026, 8:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d110627f3881908736497901a5eba8 |
completed | April 4, 2026, 1:21 p.m. |
Created at: March 30, 2026, 7:50 p.m.