Triple
T14663955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tyap language |
E344315
|
entity |
| Predicate | alternateName |
P39
|
FINISHED |
| Object |
Kataf
Kataf is an alternate name for the Tyap language, a Plateau language spoken primarily in southern Kaduna State, Nigeria.
|
E1112753
|
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: Kataf | Statement: [Tyap language, alternateName, Kataf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kataf Context triple: [Tyap language, alternateName, Kataf]
-
A.
Chufut-Kale
Chufut-Kale is a historic cave city and fortress in Crimea, known for its well-preserved medieval structures and significance to Crimean Karaite and Tatar history.
-
B.
Katafidi
Katafidi is a prominent mountain peak in the Tzoumerka range of the Pindus Mountains in northwestern Greece.
-
C.
Koufiya
Koufiya is an Arabic typeface designed by Nadine Chahine, known for its contemporary interpretation of traditional Kufic calligraphy.
-
D.
Dahan
Dahan is a critically acclaimed Bengali film directed by Rituparno Ghosh that explores themes of gender, social hypocrisy, and moral courage.
-
E.
Makadara
Makadara is a residential and commercial neighborhood in Nairobi, Kenya, known for its dense population, vibrant local markets, and mix of low- to middle-income housing.
- 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: Kataf Triple: [Tyap language, alternateName, Kataf]
Generated description
Kataf is an alternate name for the Tyap language, a Plateau language spoken primarily in southern Kaduna State, Nigeria.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kataf Target entity description: Kataf is an alternate name for the Tyap language, a Plateau language spoken primarily in southern Kaduna State, Nigeria.
-
A.
Chufut-Kale
Chufut-Kale is a historic cave city and fortress in Crimea, known for its well-preserved medieval structures and significance to Crimean Karaite and Tatar history.
-
B.
Katafidi
Katafidi is a prominent mountain peak in the Tzoumerka range of the Pindus Mountains in northwestern Greece.
-
C.
Koufiya
Koufiya is an Arabic typeface designed by Nadine Chahine, known for its contemporary interpretation of traditional Kufic calligraphy.
-
D.
Dahan
Dahan is a critically acclaimed Bengali film directed by Rituparno Ghosh that explores themes of gender, social hypocrisy, and moral courage.
-
E.
Makadara
Makadara is a residential and commercial neighborhood in Nairobi, Kenya, known for its dense population, vibrant local markets, and mix of low- to middle-income housing.
- 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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb54ae5ac81908cc69891f280e5f7 |
completed | April 14, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdd5e4789481909a64622a1d284373 |
completed | May 8, 2026, 12:24 p.m. |
| NEDg | Description generation | batch_69fdd9b5d7988190927e88feef6a972f |
completed | May 8, 2026, 12:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fddaa56f4c8190ba56af6a7a56a201 |
completed | May 8, 2026, 12:44 p.m. |
Created at: April 10, 2026, 1:27 a.m.