Triple
T6098721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaili language |
E135940
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object |
Palu Kaili
Palu Kaili is a major dialect of the Kaili language spoken around the city of Palu in Central Sulawesi, Indonesia.
|
E80399
|
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: Palu Kaili | Statement: [Kaili language, hasDialect, Palu Kaili]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Palu Kaili Context triple: [Kaili language, hasDialect, Palu Kaili]
-
A.
Sungai Penuh
Sungai Penuh is a city in the highland Kerinci region of Jambi Province on the island of Sumatra, Indonesia, known as a gateway to the Kerinci Seblat National Park.
-
B.
Bengkulu
Bengkulu is a province on the southwest coast of the Indonesian island of Sumatra, known for its Indian Ocean shoreline and colonial history.
-
C.
Dipatiukur
Dipatiukur is a central urban area in Bandung, Indonesia, known for hosting one of Universitas Padjadjaran’s main campuses and its surrounding student-oriented neighborhood.
-
D.
Padang Besar
Padang Besar is a border town in northern Malaysia known as a key land gateway and trading hub between Malaysia and Thailand.
-
E.
Palu
Palu is a coastal city on the Indonesian island of Sulawesi, known as the capital of Central Sulawesi province and a regional center for trade and administration.
- 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: Palu Kaili Triple: [Kaili language, hasDialect, Palu Kaili]
Generated description
Palu Kaili is a major dialect of the Kaili language spoken around the city of Palu in Central Sulawesi, Indonesia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Palu Kaili Target entity description: Palu Kaili is a major dialect of the Kaili language spoken around the city of Palu in Central Sulawesi, Indonesia.
-
A.
Sungai Penuh
Sungai Penuh is a city in the highland Kerinci region of Jambi Province on the island of Sumatra, Indonesia, known as a gateway to the Kerinci Seblat National Park.
-
B.
Bengkulu
Bengkulu is a province on the southwest coast of the Indonesian island of Sumatra, known for its Indian Ocean shoreline and colonial history.
-
C.
Dipatiukur
Dipatiukur is a central urban area in Bandung, Indonesia, known for hosting one of Universitas Padjadjaran’s main campuses and its surrounding student-oriented neighborhood.
-
D.
Padang Besar
Padang Besar is a border town in northern Malaysia known as a key land gateway and trading hub between Malaysia and Thailand.
-
E.
Palu
chosen
Palu is a coastal city on the Indonesian island of Sulawesi, known as the capital of Central Sulawesi province and a regional center for trade and administration.
- F. None of above.
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_69c0087cd3c48190b459848c72d84eb1 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05a9a02888190ac201acd14c3fc31 |
completed | March 22, 2026, 9:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c125475548819086b733a80056eba5 |
completed | March 23, 2026, 11:34 a.m. |
| NEDg | Description generation | batch_69c128753cd8819096edb3c817bfae10 |
completed | March 23, 2026, 11:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c129134ce08190ada54a7b3eda27f4 |
completed | March 23, 2026, 11:50 a.m. |
Created at: March 22, 2026, 4:13 p.m.