Triple
T7208218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pantar |
E148728
|
entity |
| Predicate | hasLanguage |
P15
|
FINISHED |
| Object |
Kaera language
The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
|
E650917
|
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: Kaera language | Statement: [Pantar, hasLanguage, Kaera language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaera language Context triple: [Pantar, hasLanguage, Kaera language]
-
A.
Damara language
The Damara language is a Khoe (Central Khoisan) language spoken primarily by the Damara people of Namibia.
-
B.
Hoanya language
The Hoanya language is an extinct Austronesian language once spoken by the Hoanya people of western Taiwan and classified among the indigenous Formosan languages.
-
C.
Amuesha language
The Amuesha language, also known as Yanesha', is an Arawakan language spoken by the Yanesha' people of the central Peruvian Amazon.
-
D.
Karkar-Yuri language
Karkar-Yuri is a Papuan language of Papua New Guinea, spoken by the Karkar and Yuri peoples in the Sepik region.
-
E.
Saraveca language
The Saraveca language is an extinct Arawakan language once spoken in Bolivia, known from very limited historical documentation.
- 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: Kaera language Triple: [Pantar, hasLanguage, Kaera language]
Generated description
The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kaera language Target entity description: The Kaera language is a Papuan language spoken by a small community on Pantar Island in eastern Indonesia.
-
A.
Damara language
The Damara language is a Khoe (Central Khoisan) language spoken primarily by the Damara people of Namibia.
-
B.
Hoanya language
The Hoanya language is an extinct Austronesian language once spoken by the Hoanya people of western Taiwan and classified among the indigenous Formosan languages.
-
C.
Amuesha language
The Amuesha language, also known as Yanesha', is an Arawakan language spoken by the Yanesha' people of the central Peruvian Amazon.
-
D.
Karkar-Yuri language
Karkar-Yuri is a Papuan language of Papua New Guinea, spoken by the Karkar and Yuri peoples in the Sepik region.
-
E.
Saraveca language
The Saraveca language is an extinct Arawakan language once spoken in Bolivia, known from very limited historical documentation.
- 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_69c687e8cf188190b5f3ecffd681f04e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e96ae4dc8190b0b9e064ff968c10 |
completed | March 27, 2026, 8:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7cbf0c014819088f80fccfc1d2341 |
completed | March 28, 2026, 12:39 p.m. |
| NEDg | Description generation | batch_69c7cdb372c481908a09df2107ada8c3 |
completed | March 28, 2026, 12:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7cebb70c881908e851556b678342a |
completed | March 28, 2026, 12:51 p.m. |
Created at: March 27, 2026, 2:52 p.m.