Triple
T21429344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murut language |
E528642
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object |
Paluan Murut
Paluan Murut is a regional dialect of the Murut language spoken by Murut communities in parts of Borneo.
|
E1483851
|
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: Paluan Murut | Statement: [Murut language, hasDialect, Paluan Murut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paluan Murut Context triple: [Murut language, hasDialect, Paluan Murut]
-
A.
Maanyan Dayak
Maanyan Dayak is an Austronesian language spoken by the Maanyan (Dayak) people of central Kalimantan in Indonesia.
-
B.
Munduruku
Munduruku is an indigenous people of the Brazilian Amazon known for their distinct language, rich cultural traditions, and historical prominence along the Tapajós River.
-
C.
Rungus
The Rungus are an indigenous ethnic group of northern Borneo known for their distinctive longhouse communities, intricate beadwork, and rich traditional customs.
-
D.
Bolango-Bulango
Bolango-Bulango is an Austronesian language spoken by the Bolango people in northern Sulawesi, Indonesia.
-
E.
Lembá
Lembá is a coastal district on the island of São Tomé in São Tomé and Príncipe, known for its fishing communities and lush tropical landscapes.
- 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: Paluan Murut Triple: [Murut language, hasDialect, Paluan Murut]
Generated description
Paluan Murut is a regional dialect of the Murut language spoken by Murut communities in parts of Borneo.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Paluan Murut Target entity description: Paluan Murut is a regional dialect of the Murut language spoken by Murut communities in parts of Borneo.
-
A.
Maanyan Dayak
Maanyan Dayak is an Austronesian language spoken by the Maanyan (Dayak) people of central Kalimantan in Indonesia.
-
B.
Munduruku
Munduruku is an indigenous people of the Brazilian Amazon known for their distinct language, rich cultural traditions, and historical prominence along the Tapajós River.
-
C.
Rungus
The Rungus are an indigenous ethnic group of northern Borneo known for their distinctive longhouse communities, intricate beadwork, and rich traditional customs.
-
D.
Bolango-Bulango
Bolango-Bulango is an Austronesian language spoken by the Bolango people in northern Sulawesi, Indonesia.
-
E.
Lembá
Lembá is a coastal district on the island of São Tomé in São Tomé and Príncipe, known for its fishing communities and lush tropical landscapes.
- 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_69e0c455f3688190810bc96365791b0f |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee813ef6a8819089511b8f608c9491 |
completed | April 26, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09c2ac2d188190b909826855b4d132 |
completed | May 17, 2026, 1:29 p.m. |
| NEDg | Description generation | batch_6a09c33c37e88190b559bbf98e589487 |
completed | May 17, 2026, 1:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09c3c6a208819096b2e4a2c92b3cb0 |
completed | May 17, 2026, 1:33 p.m. |
Created at: April 16, 2026, 5:49 p.m.