Triple
T7823451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siwa Berber |
E181187
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Tasiwit |
E170857
|
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: Tasiwit | Statement: [Siwa Berber, hasAlternativeName, Tasiwit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tasiwit Context triple: [Siwa Berber, hasAlternativeName, Tasiwit]
-
A.
Tasiwit
chosen
Tasiwit is an alternative name for Siwi, a Berber language spoken in Egypt’s Siwa Oasis.
-
B.
Tonsawang
Tonsawang is an Austronesian language spoken by the Tonsawang people in North Sulawesi, Indonesia.
-
C.
Thommanon
Thommanon is a small 12th-century Hindu temple in the Angkor region of Cambodia, noted for its well-preserved sandstone carvings and classical Khmer architecture.
-
D.
Tawi Sli
Tawi Sli was a Malaysian politician who served as an early Chief Minister of Sarawak during the formative years of the state's government after joining Malaysia.
-
E.
Ngam
Ngam is a dialect of the Sara language spoken by communities in parts of Central Africa, particularly in Chad and the surrounding region.
- 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_69ca8282ccec819083c48efb72d21cf9 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cafa0abff08190b0245ceca5f20cae |
completed | March 30, 2026, 10:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb14aefd4881908ffa5825f4ba6eff |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 4:42 p.m.