Triple
T1494151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siwi |
E29648
|
entity |
| Predicate | endonym |
P1435
|
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: [Siwi, endonym, Tasiwit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tasiwit Context triple: [Siwi, endonym, Tasiwit]
-
A.
Tasiwit
chosen
Tasiwit is an alternative name for Siwi, a Berber language spoken in Egypt’s Siwa Oasis.
-
B.
Tambolaka
Tambolaka is a town on the Indonesian island of Sumba that serves as an important local hub with an airport and access point for exploring the island.
-
C.
Mae Sot
Mae Sot is a Thai border town in Tak Province known as a major hub for cross-border trade and migration with Myanmar and for its numerous refugee and humanitarian aid organizations.
-
D.
Bantia
Bantia was an ancient Oscan-speaking city in southern Italy, notable for yielding important inscriptions that illuminate the Oscan language and Italic legal traditions.
-
E.
Sulak
Sulak is a Thai social activist and Buddhist scholar known for his advocacy of human rights, democracy, and engaged Buddhism.
- 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_69a498dba1d8819093b46a3a8d2485f1 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6c665488190ae665f7a1b0563f5 |
completed | March 1, 2026, 11:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad232f4b80819095a608816d4d2a34 |
completed | March 8, 2026, 7:20 a.m. |
Created at: March 1, 2026, 8:12 p.m.