Triple
T14523549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mongu |
E340711
|
entity |
| Predicate | roadConnectionTo |
P9041
|
FINISHED |
| Object | Limulunga |
E877259
|
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: Limulunga | Statement: [Mongu, roadConnectionTo, Limulunga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Limulunga Context triple: [Mongu, roadConnectionTo, Limulunga]
-
A.
Limulunga
chosen
Limulunga is a royal settlement in western Zambia that serves as one of the main capitals and ceremonial residences of the Litunga, the king of Barotseland.
-
B.
Malongo
Malongo is a major offshore oil field and production hub located off the coast of Cabinda in Angola.
-
C.
Murambi
Murambi is a residential suburb of Mutare, a major city in eastern Zimbabwe.
-
D.
Mlolongo
Mlolongo is a rapidly growing urban town in Kenya’s Machakos County, situated along the Nairobi–Mombasa highway and known for its bustling commercial activity and residential estates.
-
E.
Zamdela
Zamdela is a township suburb of Sasolburg in South Africa, primarily serving as a residential area for workers in the nearby industrial and petrochemical complexes.
- 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dea04f16f88190ba357b0f8021b46b |
completed | April 14, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8ab07e08819085a6a21cc9cea1fa |
completed | May 8, 2026, 7:03 a.m. |
Created at: April 10, 2026, 1:22 a.m.