Triple
T2874340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stevenage |
E56839
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Kadoma |
E134780
|
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: Kadoma | Statement: [Stevenage, hasTwinTown, Kadoma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kadoma Context triple: [Stevenage, hasTwinTown, Kadoma]
-
A.
Kadoma
chosen
Kadoma is a city in Osaka Prefecture, Japan, known as a residential and commercial suburb within the Osaka metropolitan area.
-
B.
Mathare
Mathare is a densely populated informal settlement and neighborhood in Nairobi, Kenya, known for its extensive slums and socio-economic challenges.
-
C.
Kisumu
Kisumu is a major Kenyan city on the shores of Lake Victoria, serving as a key commercial and transport hub in western Kenya.
-
D.
Kalangala
Kalangala is a town on Uganda’s Ssese Islands in Lake Victoria, serving as the administrative and commercial center of Kalangala District.
-
E.
Embakasi
Embakasi is a residential and industrial area in Nairobi, Kenya, known for hosting key infrastructure and serving as a major gateway corridor to the city.
- 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_69ab4a4ced288190ab6d3e062d10f7f6 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abe0032ddc8190bb4d15ec7e3c63e8 |
completed | March 7, 2026, 8:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b01db780908190919d859205464b2e |
completed | March 10, 2026, 1:33 p.m. |
Created at: March 6, 2026, 10:03 p.m.