Triple
T11578447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dogon languages |
E274563
|
entity |
| Predicate | hasSubgroup |
P747
|
FINISHED |
| Object |
Nanga
Nanga is a subgroup of the Dogon languages spoken by the Dogon people of Mali in West Africa.
|
E939904
|
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: Nanga | Statement: [Dogon languages, hasSubgroup, Nanga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nanga Context triple: [Dogon languages, hasSubgroup, Nanga]
-
A.
Mount Ntringui
Mount Ntringui is a volcanic peak on the island of Anjouan in the Comoros, known for its lush forests and prominence in the island’s rugged landscape.
-
B.
Mount Wilis
Mount Wilis is a solitary, inactive stratovolcano in East Java, Indonesia, known for its forested slopes and surrounding rural highland communities.
-
C.
Mount Adatara
Mount Adatara is an active stratovolcano in Japan’s Tohoku region, known for its scenic alpine landscapes and popular hiking trails.
-
D.
Mount Muna
Mount Muna is the highest peak on Alor Island in Indonesia, known as a prominent landmark in the island’s rugged volcanic landscape.
-
E.
Anai Mudi
Anai Mudi is the highest peak in South India, located in the Western Ghats of Kerala and known for its rich biodiversity and scenic trekking routes.
- 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: Nanga Triple: [Dogon languages, hasSubgroup, Nanga]
Generated description
Nanga is a subgroup of the Dogon languages spoken by the Dogon people of Mali in West Africa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nanga Target entity description: Nanga is a subgroup of the Dogon languages spoken by the Dogon people of Mali in West Africa.
-
A.
Mount Ntringui
Mount Ntringui is a volcanic peak on the island of Anjouan in the Comoros, known for its lush forests and prominence in the island’s rugged landscape.
-
B.
Mount Wilis
Mount Wilis is a solitary, inactive stratovolcano in East Java, Indonesia, known for its forested slopes and surrounding rural highland communities.
-
C.
Mount Adatara
Mount Adatara is an active stratovolcano in Japan’s Tohoku region, known for its scenic alpine landscapes and popular hiking trails.
-
D.
Mount Muna
Mount Muna is the highest peak on Alor Island in Indonesia, known as a prominent landmark in the island’s rugged volcanic landscape.
-
E.
Anai Mudi
Anai Mudi is the highest peak in South India, located in the Western Ghats of Kerala and known for its rich biodiversity and scenic trekking routes.
- 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_69d6aae5ac3c81908d2b0a3a665665b2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8904b46288190890ecafd6ceb0c3d |
completed | April 10, 2026, 5:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef12f0661081909c31de2c2cd304e3 |
completed | April 27, 2026, 7:40 a.m. |
| NEDg | Description generation | batch_69ef354b3b3c8190b1c91dbf9c705a7d |
completed | April 27, 2026, 10:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ef5170ce9881908f2ecf3d5ada809a |
completed | April 27, 2026, 12:07 p.m. |
Created at: April 8, 2026, 9:38 p.m.