Triple
T20443239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kalehe Territory |
E501448
|
entity |
| Predicate | hasMajorSettlement |
P316
|
FINISHED |
| Object |
Minova
Minova is a town in the eastern Democratic Republic of the Congo, situated on the shores of Lake Kivu and known as a key commercial and transit hub in South Kivu province.
|
E1431120
|
NE FINISHED |
How this triple was built (4 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: Minova | Statement: [Kalehe Territory, hasMajorSettlement, Minova]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Minova Context triple: [Kalehe Territory, hasMajorSettlement, Minova]
-
A.
Micronova
Micronova is a leading Finnish micro- and nanotechnology research and fabrication center located in Otaniemi, Espoo.
-
B.
Nutisal
Nutisal is a snack brand known for its range of dry-roasted and flavored nut products, owned by the Swedish confectionery company Cloetta.
-
C.
Founex
Founex is a small Swiss municipality on Lake Geneva in the canton of Vaud, known for its residential character and proximity to Geneva.
-
D.
Novaggio
Novaggio is a small municipality in the canton of Ticino in southern Switzerland, known for its scenic hillside setting above Lake Lugano.
-
E.
Minerva Urecal
Minerva Urecal was an American character actress known for her numerous supporting roles in film and television from the 1930s through the 1960s.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Minova Triple: [Kalehe Territory, hasMajorSettlement, Minova]
Generated description
Minova is a town in the eastern Democratic Republic of the Congo, situated on the shores of Lake Kivu and known as a key commercial and transit hub in South Kivu province.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Minova Target entity description: Minova is a town in the eastern Democratic Republic of the Congo, situated on the shores of Lake Kivu and known as a key commercial and transit hub in South Kivu province.
-
A.
Micronova
Micronova is a leading Finnish micro- and nanotechnology research and fabrication center located in Otaniemi, Espoo.
-
B.
Nutisal
Nutisal is a snack brand known for its range of dry-roasted and flavored nut products, owned by the Swedish confectionery company Cloetta.
-
C.
Founex
Founex is a small Swiss municipality on Lake Geneva in the canton of Vaud, known for its residential character and proximity to Geneva.
-
D.
Novaggio
Novaggio is a small municipality in the canton of Ticino in southern Switzerland, known for its scenic hillside setting above Lake Lugano.
-
E.
Minerva Urecal
Minerva Urecal was an American character actress known for her numerous supporting roles in film and television from the 1930s through the 1960s.
- F. None of above. chosen
Provenance (5 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_69e0b4ac0a1c81908845d0f8a56abce8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e68cfa7dd08190883a37e3480b152c |
completed | April 20, 2026, 8:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a088401774081909ac697258222235b |
completed | May 16, 2026, 2:49 p.m. |
| NEDg | Description generation | batch_6a0884aeb868819089de185429e0d99d |
completed | May 16, 2026, 2:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0885a1276c8190bc8a843386d6be6a |
completed | May 16, 2026, 2:56 p.m. |
Created at: April 16, 2026, 11:32 a.m.