Triple
T22088395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alena Mihulová |
E545846
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Alena |
E996436
|
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: Alena | Statement: [Alena Mihulová, givenName, Alena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alena Context triple: [Alena Mihulová, givenName, Alena]
-
A.
Alena
chosen
Alena is a feminine given name commonly used in Slavic countries, often considered a variant of Helena or Magdalena.
-
B.
Alisa
Alisa is a feminine given name, often considered a variant of Alice, used in various cultures around the world.
-
C.
Alisa
Alisa is the birth name of Ayn Rand, the Russian-American novelist and philosopher known for developing Objectivism and writing works such as "Atlas Shrugged" and "The Fountainhead."
-
D.
Alina
Alina is a feminine given name used in various cultures, often considered a variant of names like Aline or Adelina.
-
E.
Nadya
Nadya is a feminine given name, often used as a diminutive of Nadezhda in Slavic cultures.
- 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e3a98481908a7b3dc3f2a90276 |
completed | April 28, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a87982c6c8190af25c334ba1437d6 |
completed | May 18, 2026, 3:29 a.m. |
Created at: April 16, 2026, 8:29 p.m.