Triple
T23505031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bantawa language |
E572257
|
entity |
| Predicate | alternateName |
P39
|
FINISHED |
| Object |
Bantaba
Bantaba is an alternate name for the Bantawa language, a Kiranti language spoken primarily by the Bantawa Rai people of eastern Nepal.
|
E1588728
|
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: Bantaba | Statement: [Bantawa language, alternateName, Bantaba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bantaba Context triple: [Bantawa language, alternateName, Bantaba]
-
A.
Soppeng Regency
Soppeng Regency is an administrative region in Indonesia known for its historical Bugis culture and location in the inland area of South Sulawesi.
-
B.
Muna Regency
Muna Regency is an administrative region in Southeast Sulawesi, Indonesia, that governs much of Muna Island and surrounding areas.
-
C.
Tuban
Tuban is a coastal town and regency capital in northern East Java, Indonesia, known historically as a trading port and for its cultural and religious heritage sites.
-
D.
Tuban
Tuban is a major city in Yemen’s Lahij Governorate, serving as an important local center for administration and commerce.
-
E.
Blitar
Blitar is a city in East Java, Indonesia, best known as the hometown and final resting place of the country’s first president, Sukarno.
- 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: Bantaba Triple: [Bantawa language, alternateName, Bantaba]
Generated description
Bantaba is an alternate name for the Bantawa language, a Kiranti language spoken primarily by the Bantawa Rai people of eastern Nepal.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bantaba Target entity description: Bantaba is an alternate name for the Bantawa language, a Kiranti language spoken primarily by the Bantawa Rai people of eastern Nepal.
-
A.
Soppeng Regency
Soppeng Regency is an administrative region in Indonesia known for its historical Bugis culture and location in the inland area of South Sulawesi.
-
B.
Muna Regency
Muna Regency is an administrative region in Southeast Sulawesi, Indonesia, that governs much of Muna Island and surrounding areas.
-
C.
Tuban
Tuban is a coastal town and regency capital in northern East Java, Indonesia, known historically as a trading port and for its cultural and religious heritage sites.
-
D.
Tuban
Tuban is a major city in Yemen’s Lahij Governorate, serving as an important local center for administration and commerce.
-
E.
Blitar
Blitar is a city in East Java, Indonesia, best known as the hometown and final resting place of the country’s first president, Sukarno.
- 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_69e245b5e4208190bac8a6509867e394 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a8ff97c88190a67f787e1674619e |
completed | April 29, 2026, 6:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c8277b97481909b1405fd7469b910 |
completed | May 19, 2026, 3:32 p.m. |
| NEDg | Description generation | batch_6a0ca6f2d4288190b0b5fd46d2a387bf |
completed | May 19, 2026, 6:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ca7e9e9988190ac3bedb9ecb8ce06 |
completed | May 19, 2026, 6:11 p.m. |
Created at: April 17, 2026, 6:07 p.m.