Triple
T6786855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Papuan Tip linkage |
E155828
|
entity |
| Predicate | hasLanguage |
P15
|
FINISHED |
| Object |
Ouma language
Ouma language is an extinct Papuan language once spoken in the Papuan Tip region of southeastern Papua New Guinea.
|
E619340
|
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: Ouma language | Statement: [Papuan Tip linkage, hasLanguage, Ouma language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ouma language Context triple: [Papuan Tip linkage, hasLanguage, Ouma language]
-
A.
Uma language
Uma is an Austronesian language of the Celebic subgroup spoken primarily in Central Sulawesi, Indonesia.
-
B.
Kumbewaha language
The Kumbewaha language is an Austronesian language spoken in Sulawesi, Indonesia, belonging to the Wotu–Wolio subgroup.
-
C.
Medumba language
Medumba is a Bantu-related Grassfields language spoken primarily by the Bamileke people in western Cameroon.
-
D.
Gurma language
Gurma language is a Gur language spoken primarily in parts of Burkina Faso, Togo, Benin, and neighboring West African countries.
-
E.
Sanglechi language
The Sanglechi language is an Eastern Iranian language spoken by a small community in the Sanglech Valley region of Afghanistan and Tajikistan.
- 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: Ouma language Triple: [Papuan Tip linkage, hasLanguage, Ouma language]
Generated description
Ouma language is an extinct Papuan language once spoken in the Papuan Tip region of southeastern Papua New Guinea.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ouma language Target entity description: Ouma language is an extinct Papuan language once spoken in the Papuan Tip region of southeastern Papua New Guinea.
-
A.
Uma language
Uma is an Austronesian language of the Celebic subgroup spoken primarily in Central Sulawesi, Indonesia.
-
B.
Kumbewaha language
The Kumbewaha language is an Austronesian language spoken in Sulawesi, Indonesia, belonging to the Wotu–Wolio subgroup.
-
C.
Medumba language
Medumba is a Bantu-related Grassfields language spoken primarily by the Bamileke people in western Cameroon.
-
D.
Gurma language
Gurma language is a Gur language spoken primarily in parts of Burkina Faso, Togo, Benin, and neighboring West African countries.
-
E.
Sanglechi language
The Sanglechi language is an Eastern Iranian language spoken by a small community in the Sanglech Valley region of Afghanistan and Tajikistan.
- 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_69c6881770fc8190972b2906390380f5 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d28f043081909a9a9ab635785933 |
completed | March 27, 2026, 6:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c71a871a84819098891f66c6e5b579 |
completed | March 28, 2026, 12:02 a.m. |
| NEDg | Description generation | batch_69c71b6b87d8819085e6ae122f042626 |
completed | March 28, 2026, 12:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c71c00f86c819099ef6ae0766e9f3a |
completed | March 28, 2026, 12:08 a.m. |
Created at: March 27, 2026, 2:14 p.m.