Triple
T11469244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naro language |
E271857
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object |
Nharo
Nharo is an indigenous Khoe language spoken primarily by the Naro people of Botswana and neighboring regions in southern Africa.
|
E929620
|
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: Nharo | Statement: [Naro language, hasAlternativeName, Nharo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nharo Context triple: [Naro language, hasAlternativeName, Nharo]
-
A.
Buhera
Buhera is a rural town and district center in eastern Zimbabwe known for its agricultural activities and location within Manicaland Province.
-
B.
Nabaloi
Nabaloi is an Austronesian language spoken by the Ibaloi people of the northern Philippines, particularly in the Benguet region of Luzon.
-
C.
Xola
Xola is a Mexico City Metro station on Line 2 that serves the southern part of the city near the Calzada de Tlalpan corridor.
-
D.
Nabouwalu
Nabouwalu is a small coastal town in Fiji that serves as a key ferry and transport hub linking the island of Vanua Levu with Viti Levu.
-
E.
Kabaena
Kabaena is an island in Indonesia known for its location off the coast of Sulawesi and its mix of coastal and hilly landscapes.
- 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: Nharo Triple: [Naro language, hasAlternativeName, Nharo]
Generated description
Nharo is an indigenous Khoe language spoken primarily by the Naro people of Botswana and neighboring regions in southern Africa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nharo Target entity description: Nharo is an indigenous Khoe language spoken primarily by the Naro people of Botswana and neighboring regions in southern Africa.
-
A.
Buhera
Buhera is a rural town and district center in eastern Zimbabwe known for its agricultural activities and location within Manicaland Province.
-
B.
Nabaloi
Nabaloi is an Austronesian language spoken by the Ibaloi people of the northern Philippines, particularly in the Benguet region of Luzon.
-
C.
Xola
Xola is a Mexico City Metro station on Line 2 that serves the southern part of the city near the Calzada de Tlalpan corridor.
-
D.
Nabouwalu
Nabouwalu is a small coastal town in Fiji that serves as a key ferry and transport hub linking the island of Vanua Levu with Viti Levu.
-
E.
Kabaena
Kabaena is an island in Indonesia known for its location off the coast of Sulawesi and its mix of coastal and hilly landscapes.
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d822f74144819094479690c8151073 |
completed | April 9, 2026, 10:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6248d0db881909999049356f53ff6 |
completed | April 20, 2026, 1:05 p.m. |
| NEDg | Description generation | batch_69e62cf224f881908badcdab6aea1aef |
completed | April 20, 2026, 1:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e663ffedfc8190a2b51995c62d1e6b |
completed | April 20, 2026, 5:36 p.m. |
Created at: April 8, 2026, 9:35 p.m.