Triple
T11603340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Ġwann |
E275186
|
entity |
| Predicate | hasRoadConnectionsTo |
P11435
|
FINISHED |
| Object | Msida |
E882510
|
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: Msida | Statement: [San Ġwann, hasRoadConnectionsTo, Msida]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Msida Context triple: [San Ġwann, hasRoadConnectionsTo, Msida]
-
A.
Msida
chosen
Msida is a coastal town and local council in central Malta known for its marina, university campus, and role as a residential and commercial hub near Valletta.
-
B.
Negombo
Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
-
C.
Mambasa
Mambasa is a town and administrative center located in the forested Ituri region of northeastern Democratic Republic of the Congo.
-
D.
Maswa
Maswa is a town and administrative district in northern Tanzania, known for its agricultural activities within the Simiyu Region.
-
E.
Siaya
Siaya is a prominent town in western Kenya that serves as an administrative and commercial hub in the Nyanza 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_69d6aaf84b548190ac072e4fb89ae18f |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8954daa908190a8d532e43aa4a881 |
completed | April 10, 2026, 6:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f018eeb0f48190aea4f55d787f807a |
completed | April 28, 2026, 2:18 a.m. |
Created at: April 8, 2026, 9:38 p.m.