Triple
T7161893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Bantu |
E166965
|
entity |
| Predicate | hasMajorLanguage |
P207
|
FINISHED |
| Object | Teke |
E240267
|
NE FINISHED |
How this triple was built (2 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: [Central Bantu, hasMajorLanguage, Teke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teke Context triple: [Central Bantu, hasMajorLanguage, Teke]
-
A.
Teke
chosen
Teke is a Bantu language spoken primarily in the Republic of the Congo and neighboring Central African regions by the Teke people.
-
B.
Teke
Teke are a prominent Turkmen tribal group historically known for their influence in Central Asia and their famed Akhal-Teke horses.
-
C.
Tektitek
Tektitek is a Mayan language spoken primarily by the Tektiteko people in parts of Guatemala and Mexico.
-
D.
Teckberg
Teckberg is a prominent hill in the Swabian Jura of Baden-Württemberg, Germany, best known as the site of the historic Teck Castle overlooking the surrounding region.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c68887a5cc8190bec0ea96227164f7 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e82e4b248190ad3c3863cb93971e |
completed | March 27, 2026, 8:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7adc4b7648190969fab0351f9fd22 |
completed | March 28, 2026, 10:30 a.m. |
Created at: March 27, 2026, 2:47 p.m.