Triple
T2160278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nzebi |
E47983
|
entity |
| Predicate | hasNeighborLanguage |
P16383
|
FINISHED |
| Object |
Teke
Teke is a Bantu language spoken primarily in the Republic of the Congo and neighboring Central African regions by the Teke people.
|
E240267
|
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: Teke | Statement: [Nzebi, hasNeighborLanguage, Teke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teke Context triple: [Nzebi, hasNeighborLanguage, Teke]
-
A.
Teke
Teke are a prominent Turkmen tribal group historically known for their influence in Central Asia and their famed Akhal-Teke horses.
-
B.
Tektitek
Tektitek is a Mayan language spoken primarily by the Tektiteko people in parts of Guatemala and Mexico.
-
C.
Telu
Telu is the ISO 15924 four-letter code that represents the Telugu script used for writing the Telugu language and several other South Asian languages.
-
D.
Tianeti
Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
-
E.
Jakaltek
Jakaltek is a Mayan language spoken primarily by the Jakaltek (Popti’) people of Guatemala’s western highlands.
- 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: Teke Triple: [Nzebi, hasNeighborLanguage, Teke]
Generated description
Teke is a Bantu language spoken primarily in the Republic of the Congo and neighboring Central African regions by the Teke people.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Teke Target entity description: Teke is a Bantu language spoken primarily in the Republic of the Congo and neighboring Central African regions by the Teke people.
-
A.
Teke
Teke are a prominent Turkmen tribal group historically known for their influence in Central Asia and their famed Akhal-Teke horses.
-
B.
Tektitek
Tektitek is a Mayan language spoken primarily by the Tektiteko people in parts of Guatemala and Mexico.
-
C.
Telu
Telu is the ISO 15924 four-letter code that represents the Telugu script used for writing the Telugu language and several other South Asian languages.
-
D.
Tianeti
Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
-
E.
Jakaltek
Jakaltek is a Mayan language spoken primarily by the Jakaltek (Popti’) people of Guatemala’s western highlands.
- 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_69a88a1d1fd8819088b34990d69a712f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe8894d481908eda9363fd36fea6 |
completed | March 7, 2026, 5:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58e9ceb08190871ff9c57ece23c0 |
completed | March 9, 2026, 5:21 a.m. |
| NEDg | Description generation | batch_69ae5a3db428819083d73b4295c4e829 |
completed | March 9, 2026, 5:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae5a9b72188190bceb31975461206f |
completed | March 9, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:45 p.m.