Triple
T1375686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarawak |
E29216
|
entity |
| Predicate | hasEthnicGroup |
P1898
|
FINISHED |
| Object | Iban |
E132870
|
NE FINISHED |
How this triple was built (2 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: Iban | Statement: [Sarawak, hasEthnicGroup, Iban]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Iban Context triple: [Sarawak, hasEthnicGroup, Iban]
-
A.
Iban people
chosen
The Iban people are an indigenous Dayak ethnic group of Borneo known for their longhouse communities, rich oral traditions, and history of seafaring and warrior culture.
-
B.
Iban language
The Iban language is an Austronesian language spoken primarily by the Iban people of Borneo, especially in Sarawak, Malaysia, and parts of Kalimantan, Indonesia.
-
C.
Ibzan
Ibzan is a minor biblical judge of Israel mentioned in the Book of Judges, known for his large family and brief period of leadership.
-
D.
Riasti
Riasti is a regional dialect of the Saraiki language spoken primarily in parts of southern Punjab, Pakistan.
-
E.
Nasar
Nasar is a surname most notably associated with Sylvia Nasar, the economist and author of "A Beautiful Mind."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c2f9b51c8190ad52fd8c151499be |
completed | March 1, 2026, 10:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acde1c7e5c8190a6b999f2d5dce088 |
completed | March 8, 2026, 2:25 a.m. |
Created at: March 1, 2026, 7:59 p.m.