Triple
T1521038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tetum |
E32226
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Tetun |
E148730
|
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: Tetun | Statement: [Tetum, hasAlternativeName, Tetun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tetun Context triple: [Tetum, hasAlternativeName, Tetun]
-
A.
Tetun language
chosen
The Tetun language is an Austronesian language spoken primarily in Timor-Leste, where it serves as one of the main national and official languages.
-
B.
Mari language
The Mari language is a Uralic language spoken primarily by the Mari people in the Mari El Republic and surrounding regions of Russia, known for its distinct dialects and rich oral tradition.
-
C.
Tontemboan language
The Tontemboan language is an Austronesian language spoken by the Tontemboan people of North Sulawesi, Indonesia, and is one of the traditional Minahasan languages of the region.
-
D.
Bislama
Bislama is an English-based creole language widely spoken in Vanuatu and used as a key lingua franca across its many islands and communities.
-
E.
Tetum
Tetum is an Austronesian language and one of the official languages of Timor-Leste, widely used in government, education, and daily communication.
- 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_69a885e9b0ac819093a9806ad0efc82c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a907f071848190a5fb8fa1b97ef4de |
completed | March 5, 2026, 4:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad468cd3b88190916a6363884d664b |
completed | March 8, 2026, 9:51 a.m. |
Created at: March 4, 2026, 7:26 p.m.