Triple
T7798586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kołobrzeg |
E180362
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Hvidovre |
E476077
|
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: Hvidovre | Statement: [Kołobrzeg, hasTwinTown, Hvidovre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hvidovre Context triple: [Kołobrzeg, hasTwinTown, Hvidovre]
-
A.
Hvidovre
chosen
Hvidovre is a suburban municipality in the Capital Region of Denmark, located just southwest of central Copenhagen.
-
B.
Valby
Valby is a district in Copenhagen, Denmark, known as an important local transport and residential area within the city.
-
C.
Ennore
Ennore is a coastal industrial and port suburb in the northern part of Chennai, Tamil Nadu, India.
-
D.
Ballerup
Ballerup is a suburban municipality near Copenhagen in eastern Denmark, known for its residential areas, business parks, and sports facilities.
-
E.
Høje Taastrup
Høje Taastrup is a major suburban railway and transport hub in the western part of the Copenhagen metropolitan area.
- 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_69ca827d22208190b4dc5aa680edcf5d |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cae984185881908117f9f549ffc443 |
completed | March 30, 2026, 9:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb14149abc8190b172cfa8ab3b0fba |
completed | March 31, 2026, 12:23 a.m. |
Created at: March 30, 2026, 4:32 p.m.