Triple
T2253340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Assyrian Neo-Aramaic |
E49663
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Suret |
E247169
|
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: Suret | Statement: [Assyrian Neo-Aramaic, alternativeName, Suret]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Suret Context triple: [Assyrian Neo-Aramaic, alternativeName, Suret]
-
A.
Suret
chosen
Suret is a modern Eastern Neo-Aramaic language spoken primarily by Assyrian communities in parts of Iraq, Syria, Iran, and the global diaspora.
-
B.
Gilot
Gilot is a French surname most notably borne by Françoise Gilot, the painter and writer known for her long relationship with Pablo Picasso.
-
C.
Jahra
Jahra is a major town and administrative center in western Kuwait, known historically as an agricultural area and now as a growing suburban and commercial hub.
-
D.
Bertogne
Bertogne is a rural municipality in the Luxembourg province of Wallonia in southeastern Belgium.
-
E.
Sauvestre
Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
- 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_69a88aaa9250819095e127d0d77e8a32 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc12029548190af9f2cdd7a4de2d6 |
completed | March 7, 2026, 6:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71c487908190903e06bcb2393484 |
completed | March 9, 2026, 7:07 a.m. |
Created at: March 4, 2026, 7:47 p.m.