Triple
T5283495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sasak |
E119554
|
entity |
| Predicate | hasDialects |
P4251
|
FINISHED |
| Object |
Mriak-Mriku
Mriak-Mriku is a regional dialect of the Sasak language spoken by communities on the island of Lombok in Indonesia.
|
E508402
|
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: Mriak-Mriku | Statement: [Sasak, hasDialects, Mriak-Mriku]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mriak-Mriku Context triple: [Sasak, hasDialects, Mriak-Mriku]
-
A.
Munnik
Munnik is a given name associated with J. B. M. Hertzog, a prominent early 20th-century South African prime minister and political leader.
-
B.
Mukerian
Mukerian is a town and municipal council in the Indian state of Punjab, known for its strategic location near the Beas River and the Mukerian Hydel Project.
-
C.
Mokre
Mokre is a district of the town of Mikołów in southern Poland, situated in the Silesian region.
-
D.
Mirik
Mirik is a small hill town and popular tourist destination in the Darjeeling district of West Bengal, India, known for its scenic lake, tea gardens, and pleasant climate.
-
E.
Mugatu
Mugatu is the flamboyant, villainous fashion designer portrayed by Will Ferrell in the comedy film "Zoolander."
- 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: Mriak-Mriku Triple: [Sasak, hasDialects, Mriak-Mriku]
Generated description
Mriak-Mriku is a regional dialect of the Sasak language spoken by communities on the island of Lombok in Indonesia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mriak-Mriku Target entity description: Mriak-Mriku is a regional dialect of the Sasak language spoken by communities on the island of Lombok in Indonesia.
-
A.
Munnik
Munnik is a given name associated with J. B. M. Hertzog, a prominent early 20th-century South African prime minister and political leader.
-
B.
Mukerian
Mukerian is a town and municipal council in the Indian state of Punjab, known for its strategic location near the Beas River and the Mukerian Hydel Project.
-
C.
Mokre
Mokre is a district of the town of Mikołów in southern Poland, situated in the Silesian region.
-
D.
Mirik
Mirik is a small hill town and popular tourist destination in the Darjeeling district of West Bengal, India, known for its scenic lake, tea gardens, and pleasant climate.
-
E.
Mugatu
Mugatu is the flamboyant, villainous fashion designer portrayed by Will Ferrell in the comedy film "Zoolander."
- 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_69bd446d05a8819092ad333a3f9c8d5c |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd84c8d2bc8190840699e5a526b756 |
completed | March 20, 2026, 5:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf06e6200881908da623e8548ec051 |
completed | March 21, 2026, 9 p.m. |
| NEDg | Description generation | batch_69bf09d1b9088190a7bf560c8d22d225 |
completed | March 21, 2026, 9:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf0a77e3b88190904c5ed6ee48ee71 |
completed | March 21, 2026, 9:15 p.m. |
Created at: March 20, 2026, 1:52 p.m.