Triple
T3004594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montreux |
E81869
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Plovdiv |
E191700
|
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: Plovdiv | Statement: [Montreux, hasTwinTown, Plovdiv]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Plovdiv Context triple: [Montreux, hasTwinTown, Plovdiv]
-
A.
Plovdiv
chosen
Plovdiv is Bulgaria’s second-largest city and one of Europe’s oldest continuously inhabited urban centers, known for its Roman amphitheater, Old Town, and rich cultural heritage.
-
B.
Burgas
Burgas is a major Bulgarian city and industrial center on the Black Sea coast, known for its large seaport and role as a key maritime and logistics hub in the region.
-
C.
Blagoevgrad
Blagoevgrad is a city in southwestern Bulgaria known as a regional cultural and educational center, home to several universities and a vibrant student population.
-
D.
Tarnovo
Tarnovo, often called Veliko Tarnovo, is a historic Bulgarian city famed as a medieval capital and cultural stronghold, known for its dramatic hillside setting and well-preserved architectural heritage.
-
E.
Varna
Varna is a major Bulgarian city on the Black Sea coast known as an important economic, cultural, and maritime center.
- 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_69ad8b1c4de88190a83b7cefaa1f2842 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a149b248190ac4f11afc4871cc1 |
completed | March 8, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b12e56bbd881909680248acca30557 |
completed | March 11, 2026, 8:56 a.m. |
Created at: March 8, 2026, 2:59 p.m.