Triple
T10837224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daju Mongo |
E255791
|
entity |
| Predicate | hasAncestor |
P369
|
FINISHED |
| Object |
Proto-Daju
Proto-Daju is the reconstructed ancestral language from which the modern Daju languages, including Daju Mongo, are derived.
|
E889281
|
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: Proto-Daju | Statement: [Daju Mongo, hasAncestor, Proto-Daju]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Proto-Daju Context triple: [Daju Mongo, hasAncestor, Proto-Daju]
-
A.
Proto-Min
Proto-Min is the reconstructed common ancestor of the Min group of Sinitic languages, representing an early stage of Chinese spoken in southeastern China before significant later divergences.
-
B.
Proto-Koman
Proto-Koman is the reconstructed ancestral language from which the modern Koman languages of the Nilo-Saharan family are derived.
-
C.
Daju Mongo
Daju Mongo is a Daju language spoken primarily in Chad and Sudan, belonging to the Eastern Sudanic branch of the Nilo-Saharan language family.
-
D.
Jawoyn
Jawoyn is an Aboriginal Australian people and their associated language from the Northern Territory, particularly around the Katherine region.
-
E.
Dadu’a
Dadu’a is an indigenous local language spoken on Atauro Island, part of Timor-Leste.
- 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: Proto-Daju Triple: [Daju Mongo, hasAncestor, Proto-Daju]
Generated description
Proto-Daju is the reconstructed ancestral language from which the modern Daju languages, including Daju Mongo, are derived.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Proto-Daju Target entity description: Proto-Daju is the reconstructed ancestral language from which the modern Daju languages, including Daju Mongo, are derived.
-
A.
Proto-Min
Proto-Min is the reconstructed common ancestor of the Min group of Sinitic languages, representing an early stage of Chinese spoken in southeastern China before significant later divergences.
-
B.
Proto-Koman
Proto-Koman is the reconstructed ancestral language from which the modern Koman languages of the Nilo-Saharan family are derived.
-
C.
Daju Mongo
Daju Mongo is a Daju language spoken primarily in Chad and Sudan, belonging to the Eastern Sudanic branch of the Nilo-Saharan language family.
-
D.
Jawoyn
Jawoyn is an Aboriginal Australian people and their associated language from the Northern Territory, particularly around the Katherine region.
-
E.
Dadu’a
Dadu’a is an indigenous local language spoken on Atauro Island, part of Timor-Leste.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d746ff70148190b844ab92d796af6c |
completed | April 9, 2026, 6:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb12aae648190aa7c93cee60ae3ea |
completed | April 14, 2026, 9:27 p.m. |
| NEDg | Description generation | batch_69dec2534728819095b3693120772da9 |
completed | April 14, 2026, 10:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69dec79b1b548190a74312284f98551c |
completed | April 14, 2026, 11:02 p.m. |
Created at: April 8, 2026, 9:19 p.m.