Triple
T7788004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tisiway |
E187295
|
entity |
| Predicate | hasEthnologueEntry |
P19233
|
FINISHED |
| Object | Siwi (siz) |
E29648
|
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: Siwi (siz) | Statement: [Tisiway, hasEthnologueEntry, Siwi (siz)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Siwi (siz) Context triple: [Tisiway, hasEthnologueEntry, Siwi (siz)]
-
A.
Siwi
chosen
Siwi is a Berber language spoken primarily in Egypt’s Siwa Oasis, known for its unique features and relative isolation from other Berber varieties.
-
B.
Siwan
Siwan is a town and district headquarters in the Indian state of Bihar, known for its historical significance and political prominence.
-
C.
Siwan
Siwan is the Welsh name for Joan, Lady of Wales, the illegitimate daughter of King John of England and wife of Llywelyn the Great.
-
D.
SWI
SWI is the National Rail station code for Swindon railway station in Wiltshire, England.
-
E.
Siyavash
Siyavash is a tragic prince and hero in the Persian epic Shahnameh, renowned for his innocence, loyalty, and unjust death.
- 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_69ca82af2d2c8190963861f5e0b8bf21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cae7e779ec8190b77296d9c2ac3210 |
completed | March 30, 2026, 9:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb139fdf188190b1c80dd6d008c34d |
completed | March 31, 2026, 12:21 a.m. |
Created at: March 30, 2026, 4:24 p.m.