Triple
T15427329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Horsens |
E369544
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Kunda |
E813200
|
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: Kunda | Statement: [Horsens, hasTwinTown, Kunda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kunda Context triple: [Horsens, hasTwinTown, Kunda]
-
A.
Kunda
chosen
Kunda is a small industrial town in northern Estonia known for its cement industry and archaeological significance.
-
B.
Kaonde
Kaonde is a Bantu language spoken primarily by the Kaonde people of northwestern Zambia and parts of the Democratic Republic of the Congo.
-
C.
Lunda
Lunda is a Bantu language spoken primarily by the Lunda people in parts of Zambia, Angola, and the Democratic Republic of the Congo.
-
D.
Kindu
Kindu is a city in the eastern Democratic Republic of the Congo that serves as the capital of Maniema Province and an important regional transport hub.
-
E.
Yundum
Yundum is a town in The Gambia known for its international airport and proximity to the capital, Banjul.
- 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_69d85a1849f48190bf898068b2806fae |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ec31f4881908b26ff7c381d7bc9 |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff21a18c548190b8591776828c1793 |
completed | May 9, 2026, 11:59 a.m. |
Created at: April 10, 2026, 3:20 a.m.