Triple
T16663990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taracahitic languages |
E404932
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Temori language
The Temori language is an indigenous Uto-Aztecan language historically spoken by a small community in northern Mexico.
|
E1226017
|
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: Temori language | Statement: [Taracahitic languages, hasMember, Temori language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Temori language Context triple: [Taracahitic languages, hasMember, Temori language]
-
A.
Keiga language
The Keiga language is a Kadu (Kadugli) language spoken by the Keiga people in the Nuba Mountains region of Sudan.
-
B.
Towa language
Towa is a Native American language spoken by the Towa (Jemez) people of New Mexico and is part of the Puebloan language family.
-
C.
Chimariko language
The Chimariko language is an extinct Native American language once spoken in northwestern California, often classified within the proposed Hokan language family.
-
D.
Kaera language
The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
-
E.
Ahirani language
Ahirani language is an Indo-Aryan language spoken primarily in the Khandesh region of Maharashtra, India, known for its close relation to Marathi and distinct regional dialectal features.
- 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: Temori language Triple: [Taracahitic languages, hasMember, Temori language]
Generated description
The Temori language is an indigenous Uto-Aztecan language historically spoken by a small community in northern Mexico.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Temori language Target entity description: The Temori language is an indigenous Uto-Aztecan language historically spoken by a small community in northern Mexico.
-
A.
Keiga language
The Keiga language is a Kadu (Kadugli) language spoken by the Keiga people in the Nuba Mountains region of Sudan.
-
B.
Towa language
Towa is a Native American language spoken by the Towa (Jemez) people of New Mexico and is part of the Puebloan language family.
-
C.
Chimariko language
The Chimariko language is an extinct Native American language once spoken in northwestern California, often classified within the proposed Hokan language family.
-
D.
Kaera language
The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
-
E.
Ahirani language
Ahirani language is an Indo-Aryan language spoken primarily in the Khandesh region of Maharashtra, India, known for its close relation to Marathi and distinct regional dialectal features.
- 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37c9afd048190b73bbc9c423915ca |
completed | April 18, 2026, 12:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0084d091e0819088a98ef4aa775d07 |
completed | May 10, 2026, 1:14 p.m. |
| NEDg | Description generation | batch_6a008585ba6c8190b5c870ebe1c93ffc |
completed | May 10, 2026, 1:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a008624706881909e9a265a37eeb3fc |
completed | May 10, 2026, 1:20 p.m. |
Created at: April 10, 2026, 5:18 a.m.