Triple
T7833554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brandýs nad Labem-Stará Boleslav |
E181632
|
entity |
| Predicate | twinTownType |
P42171
|
FINISHED |
| Object | twin town |
—
|
LITERAL 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: twin town | Statement: [Brandýs nad Labem-Stará Boleslav, twinTownType, twin town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: twinTownType Context triple: [Brandýs nad Labem-Stará Boleslav, twinTownType, twin town]
-
A.
twinType
chosen
Indicates that one entity is classified as a specific type or category of twin in relation to another entity.
-
B.
hasTwinTown
Indicates that two towns or cities are officially paired in a twinning relationship, typically for cultural, social, or economic exchange.
-
C.
hasTwinCityStructure
Indicates that one city has an officially recognized twin-city (sister-city) relationship structure with another city.
-
D.
twinCity
Indicates that two cities are officially recognized as twin (or sister) cities, typically signifying a formal partnership for cultural, economic, or social exchange.
-
E.
hasArchitecturalTwin
Indicates that two entities share nearly identical architectural design, form, or structure, effectively making them architectural counterparts or duplicates.
- F. None of above.
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_69ca8284a25c8190a1a20afad30da792 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb064a47648190af2ca2b336584a92 |
completed | March 30, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69cae91e98988190abd4ece75932c589 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:45 p.m.