Triple
T13339793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sasson |
E317793
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Sason |
E728080
|
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: Sason | Statement: [Sasson, hasVariant, Sason]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sason Context triple: [Sasson, hasVariant, Sason]
-
A.
Sason
Sason is a surname most notably associated with Swedish industrial designer Sixten Sason, known for his influential work with Saab automobiles.
-
B.
Sason
chosen
Sason is a town and district in Batman Province in southeastern Turkey, historically known as Sassoun and noted for its Armenian cultural heritage and mountainous terrain.
-
C.
Sarnıç
Sarnıç is a short story collection by renowned Turkish writer Sait Faik Abasıyanık, known for its vivid portrayals of everyday life and marginalized characters in Istanbul.
-
D.
Sarikoli
Sarikoli is an Eastern Iranian language spoken primarily by the Tajik ethnic community in the Tashkurgan region of Xinjiang, China.
-
E.
Demerdzhi
Demerdzhi is a notable mountain massif in Crimea, famous for its striking rock formations and scenic landscapes.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99d01bf8481908cd3a99e5557b972 |
completed | April 11, 2026, 12:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f3ecf4c8190bb9eee699859dc08 |
completed | May 3, 2026, 10:11 a.m. |
Created at: April 9, 2026, 9:31 p.m.