Triple
T12850677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sándor |
E307307
|
entity |
| Predicate | hasRelatedName |
P3889
|
FINISHED |
| Object | Sasha |
E40409
|
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: Sasha | Statement: [Sándor, hasRelatedName, Sasha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sasha Context triple: [Sándor, hasRelatedName, Sasha]
-
A.
Sasha
Sasha is a renowned British DJ and record producer known for his influential role in the development of progressive house and trance music.
-
B.
Sasha
Sasha is a sharp-witted Pandoran con artist and key supporting protagonist in the episodic graphic adventure game Tales from the Borderlands.
-
C.
Sasha
Sasha is a charismatic, gender-fluid Russian nobleman and love interest in Virginia Woolf’s novel "Orlando: A Biography."
-
D.
Sasha
chosen
Sasha is a common Russian diminutive form of the given name Alexander (and also Alexandra).
-
E.
Sasha
Sasha is one of the costumed cougar mascots representing the University of Houston's athletic teams, the Houston Cougars.
- 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_69d7bdf5e7cc8190be357278bc5ba3bb |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97020eacc81909357b3398d17dc49 |
completed | April 10, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a549fc188190a7dfcf16faa5e415 |
completed | May 3, 2026, 1:30 a.m. |
Created at: April 9, 2026, 5:36 p.m.