Triple
T14870026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maputo Railway Station |
E349718
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | city of Maputo |
E70168
|
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: city of Maputo | Statement: [Maputo Railway Station, serves, city of Maputo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: city of Maputo Context triple: [Maputo Railway Station, serves, city of Maputo]
-
A.
Maputo
chosen
Maputo is the largest city and main economic and cultural center of Mozambique, located on the country’s southern coast along the Indian Ocean.
-
B.
Nampula
Nampula is a major city in northern Mozambique that serves as an important commercial and transportation hub for the region.
-
C.
Malaba
Malaba is a key border town between Uganda and Kenya that serves as a major transit point for regional trade and transport.
-
D.
Masvingo
Masvingo is one of Zimbabwe’s oldest urban centers, located in the country’s southeastern region near the Great Zimbabwe ruins.
-
E.
Beira
Beira is a major port city in central Mozambique, serving as a key commercial and transport hub for the region.
- 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded57967748190a7c05ebb74aacb7c |
completed | April 15, 2026, 12:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe651067cc8190b9c218ef1f802762 |
completed | May 8, 2026, 10:34 p.m. |
Created at: April 10, 2026, 1:55 a.m.