Triple
T6469535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tupi–Guaraní |
E142312
|
entity |
| Predicate | hasLanguage |
P15
|
FINISHED |
| Object |
Emerillon (Teko)
Emerillon (Teko) is an indigenous Tupi–Guaraní language spoken by the Teko people of French Guiana.
|
E596800
|
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: Emerillon (Teko) | Statement: [Tupi–Guaraní, hasLanguage, Emerillon (Teko)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emerillon (Teko) Context triple: [Tupi–Guaraní, hasLanguage, Emerillon (Teko)]
-
A.
Brecheret
Brecheret is the surname of Victor Brecheret, a prominent Italian-Brazilian modernist sculptor known for his monumental public works in Brazil.
-
B.
Teke
Teke is a Bantu language spoken primarily in the Republic of the Congo and neighboring Central African regions by the Teke people.
-
C.
Teke
Teke are a prominent Turkmen tribal group historically known for their influence in Central Asia and their famed Akhal-Teke horses.
-
D.
The Turim
The Turim is a foundational 14th-century Jewish legal code by Rabbi Jacob ben Asher that systematically organizes halakhic rulings into four major sections.
-
E.
Echenique
Echenique is a Spanish-language surname of Basque origin borne by various notable figures in politics, arts, and public life across the Spanish-speaking world.
- 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: Emerillon (Teko) Triple: [Tupi–Guaraní, hasLanguage, Emerillon (Teko)]
Generated description
Emerillon (Teko) is an indigenous Tupi–Guaraní language spoken by the Teko people of French Guiana.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Emerillon (Teko) Target entity description: Emerillon (Teko) is an indigenous Tupi–Guaraní language spoken by the Teko people of French Guiana.
-
A.
Brecheret
Brecheret is the surname of Victor Brecheret, a prominent Italian-Brazilian modernist sculptor known for his monumental public works in Brazil.
-
B.
Teke
Teke is a Bantu language spoken primarily in the Republic of the Congo and neighboring Central African regions by the Teke people.
-
C.
Teke
Teke are a prominent Turkmen tribal group historically known for their influence in Central Asia and their famed Akhal-Teke horses.
-
D.
The Turim
The Turim is a foundational 14th-century Jewish legal code by Rabbi Jacob ben Asher that systematically organizes halakhic rulings into four major sections.
-
E.
Echenique
Echenique is a Spanish-language surname of Basque origin borne by various notable figures in politics, arts, and public life across the Spanish-speaking world.
- 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_69c008d3bf4c8190bcf798c5ba9d6fb3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06a16272c81909313455002cd884d |
completed | March 22, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6539a16648190ba5146a292d61ce7 |
completed | March 27, 2026, 9:53 a.m. |
| NEDg | Description generation | batch_69c6578825d88190a7f9da7a4f3cdfc9 |
completed | March 27, 2026, 10:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c657e45ff88190a169e159bba142f5 |
completed | March 27, 2026, 10:11 a.m. |
Created at: March 22, 2026, 4:50 p.m.