Triple
T6728242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bima language |
E153570
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object |
Nggahi Mbojo
Nggahi Mbojo is an Austronesian language spoken primarily by the Bima people on the eastern part of Sumbawa Island in Indonesia.
|
E615571
|
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: Nggahi Mbojo | Statement: [Bima language, alternativeName, Nggahi Mbojo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nggahi Mbojo Context triple: [Bima language, alternativeName, Nggahi Mbojo]
-
A.
Obo Monobo
Obo Monobo is a subgroup of the Manobo languages spoken by an indigenous community in the Philippines.
-
B.
Mambo
Mambo is an open-source content management system that was widely used in the early 2000s for building dynamic websites and later served as the codebase origin for Joomla!.
-
C.
Ngeno-Ngene
Ngeno-Ngene is a major dialect of the Sasak language spoken on the island of Lombok in Indonesia.
-
D.
Ini Kamoze
Ini Kamoze is a Jamaican reggae and dancehall singer best known internationally for his 1994 hit single "Here Comes the Hotstepper."
-
E.
Mambo Mouth
Mambo Mouth is a one-man off-Broadway stage show by John Leguizamo in which he portrays multiple Latino characters in a fast-paced, comedic performance.
- 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: Nggahi Mbojo Triple: [Bima language, alternativeName, Nggahi Mbojo]
Generated description
Nggahi Mbojo is an Austronesian language spoken primarily by the Bima people on the eastern part of Sumbawa Island in Indonesia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nggahi Mbojo Target entity description: Nggahi Mbojo is an Austronesian language spoken primarily by the Bima people on the eastern part of Sumbawa Island in Indonesia.
-
A.
Obo Monobo
Obo Monobo is a subgroup of the Manobo languages spoken by an indigenous community in the Philippines.
-
B.
Mambo
Mambo is an open-source content management system that was widely used in the early 2000s for building dynamic websites and later served as the codebase origin for Joomla!.
-
C.
Ngeno-Ngene
Ngeno-Ngene is a major dialect of the Sasak language spoken on the island of Lombok in Indonesia.
-
D.
Ini Kamoze
Ini Kamoze is a Jamaican reggae and dancehall singer best known internationally for his 1994 hit single "Here Comes the Hotstepper."
-
E.
Mambo Mouth
Mambo Mouth is a one-man off-Broadway stage show by John Leguizamo in which he portrays multiple Latino characters in a fast-paced, comedic performance.
- 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_69c6880afb988190ad88011b48ecfcba |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d153ef9c8190a31021227d814d82 |
completed | March 27, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70afea37881909a4fdce4b3229e38 |
completed | March 27, 2026, 10:55 p.m. |
| NEDg | Description generation | batch_69c70be7d9308190b7e4e36e89c12773 |
completed | March 27, 2026, 10:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c70c618a2c819097e0cfd869bf99b7 |
completed | March 27, 2026, 11:01 p.m. |
Created at: March 27, 2026, 2:08 p.m.