Triple
T2821497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basilicata |
E54819
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Matera |
E304593
|
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: Matera | Statement: [Basilicata, contains, Matera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matera Context triple: [Basilicata, contains, Matera]
-
A.
Matera
chosen
Matera is a historic city in southern Italy renowned for its ancient cave dwellings, the Sassi, a UNESCO World Heritage Site.
-
B.
Nocera Umbra
Nocera Umbra is a historic hill town in the Umbria region of central Italy, known for its medieval architecture and mineral springs.
-
C.
Otranto
Otranto is a historic coastal town in southern Italy’s Apulia region, known for its medieval castle, cathedral, and strategic position on the Adriatic Sea.
-
D.
Frascati
Frascati is a historic town in the Alban Hills near Rome, Italy, renowned for its white wine, Renaissance villas, and scenic views over the capital.
-
E.
Melfi
Melfi is a historic town in southern Italy known as an important medieval center of Norman rule and site of several papal councils.
- 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_69ab49e100c0819082a40cb797383243 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde704af88190a132626acc99745f |
completed | March 7, 2026, 8:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0312dd4848190b30f6fcc11c2c954 |
completed | March 10, 2026, 2:56 p.m. |
Created at: March 6, 2026, 9:59 p.m.