Triple
T2878391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aleksander |
E56933
|
entity |
| Predicate | hasShortForm |
P43
|
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: [Aleksander, hasShortForm, Sasha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sasha Context triple: [Aleksander, hasShortForm, Sasha]
-
A.
Sasha
chosen
Sasha is a common Russian diminutive form of the given name Alexander (and also Alexandra).
-
B.
Sasha
Sasha is one of the costumed cougar mascots representing the University of Houston's athletic teams, the Houston Cougars.
-
C.
Misha
Misha is the bear mascot of the 1980 Moscow Summer Olympics, widely remembered for its iconic, sentimental farewell during the closing ceremony.
-
D.
Sonya
Sonya is a gentle, selfless young woman in Leo Tolstoy’s novel "War and Peace," known for her unrequited love and quiet loyalty to the Rostov family.
-
E.
Tanya
Tanya is the foundational Chabad-Lubavitch Hasidic work by Rabbi Shneur Zalman of Liadi, presenting a systematic approach to Jewish mysticism, psychology, and spiritual self-improvement.
- 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_69ab4a4ced288190ab6d3e062d10f7f6 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abe008925c81909683d0ebc6227e5e |
completed | March 7, 2026, 8:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b03158d0ec8190ba9675ece8f62033 |
completed | March 10, 2026, 2:57 p.m. |
Created at: March 6, 2026, 10:03 p.m.