Triple
T9749402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bittou |
E236400
|
entity |
| Predicate | hasTownTwinningWith |
P31399
|
FINISHED |
| Object | European municipalities |
—
|
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: European municipalities | Statement: [Bittou, hasTownTwinningWith, European municipalities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTownTwinningWith Context triple: [Bittou, hasTownTwinningWith, European municipalities]
-
A.
hasTwinTown
Indicates that two towns or cities are officially paired in a twinning relationship, typically for cultural, social, or economic exchange.
-
B.
sisterMunicipalityWith
chosen
Indicates a formal partnership or twinning relationship between two municipalities, typically for cultural, social, or economic cooperation.
-
C.
sisterCityCountry
Indicates that a city has an official sister-city relationship with a city located in the specified country.
-
D.
isNeighboringCityOf
Indicates that one city is geographically adjacent to or directly borders another city.
-
E.
hasSisterCityRelationshipType
Indicates a formal sister-city partnership relationship that exists between two municipalities or cities.
- 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_69ca84d4eddc8190996fec1417d2bae8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9f6a2f8c8190a6f6af6587ee90b8 |
completed | April 1, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69cd03cc128c81908b84ef224f858b4e |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:23 p.m.