Triple
T15277976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tucanoan languages |
E365192
|
entity |
| Predicate | hasMemberLanguage |
P7390
|
FINISHED |
| Object |
Makuna
Makuna is an indigenous Tucanoan language spoken by the Makuna people of the northwest Amazon region, primarily in Colombia and Brazil.
|
E1151650
|
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: Makuna | Statement: [Tucanoan languages, hasMemberLanguage, Makuna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Makuna Context triple: [Tucanoan languages, hasMemberLanguage, Makuna]
-
A.
Marangona
Marangona is the largest and most famous bell of St Mark's Campanile in Venice, traditionally used to mark the beginning and end of the working day and to signal important civic events.
-
B.
Makun
Makun is a residential suburb within the city of Sagamu in Ogun State, southwestern Nigeria.
-
C.
Makilala
Makilala is a municipality in the province of North Cotabato in the Philippines, known for its agricultural economy and proximity to Mount Apo.
-
D.
Makato
Makato is a coastal municipality in the province of Aklan in the Western Visayas region of the Philippines.
-
E.
Mokuola
Mokuola is a small, lush island in Hilo Bay on Hawaii’s Big Island, known for its tranquil park, tidal pools, and scenic views of the bay and Mauna Kea.
- 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: Makuna Triple: [Tucanoan languages, hasMemberLanguage, Makuna]
Generated description
Makuna is an indigenous Tucanoan language spoken by the Makuna people of the northwest Amazon region, primarily in Colombia and Brazil.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Makuna Target entity description: Makuna is an indigenous Tucanoan language spoken by the Makuna people of the northwest Amazon region, primarily in Colombia and Brazil.
-
A.
Marangona
Marangona is the largest and most famous bell of St Mark's Campanile in Venice, traditionally used to mark the beginning and end of the working day and to signal important civic events.
-
B.
Makun
Makun is a residential suburb within the city of Sagamu in Ogun State, southwestern Nigeria.
-
C.
Makilala
Makilala is a municipality in the province of North Cotabato in the Philippines, known for its agricultural economy and proximity to Mount Apo.
-
D.
Makato
Makato is a coastal municipality in the province of Aklan in the Western Visayas region of the Philippines.
-
E.
Mokuola
Mokuola is a small, lush island in Hilo Bay on Hawaii’s Big Island, known for its tranquil park, tidal pools, and scenic views of the bay and Mauna Kea.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00953bc848190b83919f39d5ee37b |
completed | April 15, 2026, 9:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01e092408190aec1561e78ea0acb |
completed | May 9, 2026, 9:44 a.m. |
| NEDg | Description generation | batch_69ff028330688190b9ff26d1f349bcf9 |
completed | May 9, 2026, 9:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff042899fc8190b784d2d2ff1760e7 |
completed | May 9, 2026, 9:53 a.m. |
Created at: April 10, 2026, 3:14 a.m.