Triple
T3730038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patras |
E79038
|
entity |
| Predicate | twinnedWith |
P1072
|
FINISHED |
| Object | Bari |
E29192
|
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: Bari | Statement: [Patras, twinnedWith, Bari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bari Context triple: [Patras, twinnedWith, Bari]
-
A.
Bari
chosen
Bari is a major port city in southern Italy that served as an important Allied military hub and logistics center during World War II.
-
B.
Brindisi
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.
-
C.
Pescara
Pescara is a coastal city in the Abruzzo region of central Italy, known for its Adriatic beaches, modern urban layout, and role as a commercial and tourist hub.
-
D.
Ancona
Ancona is a historic port city on Italy’s Adriatic coast, notable for its long-standing Jewish community and role as a commercial and cultural crossroads.
-
E.
Livorno
Livorno is a port city on Italy’s western coast, historically notable for its diverse communities and significant Jewish population.
- 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_69ad8b0e4650819090ad7cef094285e8 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb1bb5408190990ea4dfbdab5c68 |
completed | March 8, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b589bcbce88190b97b9dcec8a976f4 |
completed | March 14, 2026, 4:15 p.m. |
Created at: March 8, 2026, 3:34 p.m.