Triple
T7344003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ENEA |
E169327
|
entity |
| Predicate | hasOfficeIn |
P1268
|
FINISHED |
| Object | Brindisi |
E131131
|
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: Brindisi | Statement: [ENEA, hasOfficeIn, Brindisi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brindisi Context triple: [ENEA, hasOfficeIn, Brindisi]
-
A.
Brindisi
chosen
Brindisi is a historic port city in southern Italy’s Apulia region, long serving as a key maritime gateway between Italy and the eastern Mediterranean.
-
B.
Lecce
Lecce is a historic city in Italy’s Apulia region, renowned for its rich Baroque architecture and cultural heritage.
-
C.
Molfetta
Molfetta is a coastal city in the Apulia region of southern Italy, known for its historic old town, fishing port, and Adriatic seaside location.
-
D.
Taranto
Taranto is a historic coastal city in southern Italy known as a major naval and commercial hub and for its strategic position on the Gulf of Taranto.
-
E.
Barletta
Barletta is a historic coastal city in the Apulia region of southern Italy, known for its medieval architecture and role as a provincial capital.
- 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_69c68a57710481909f0c1f3c6ebdb6f2 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0ed78908190a169f094cb3f62f0 |
completed | March 27, 2026, 9:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c856a22b208190821bcbf21a074bb8 |
completed | March 28, 2026, 10:30 p.m. |
Created at: March 27, 2026, 3:05 p.m.