Triple
T3899469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivan Hlinka |
E90449
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ivan |
E157814
|
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: Ivan | Statement: [Ivan Hlinka, givenName, Ivan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ivan Context triple: [Ivan Hlinka, givenName, Ivan]
-
A.
Ivan
chosen
Ivan is a common Slavic male given name widely used in Russia and other Eastern European countries, equivalent to "John" in English.
-
B.
Vasily
Vasily is a masculine given name of Slavic origin, commonly used in Russian-speaking countries.
-
C.
Fyodor
Fyodor is a masculine given name of Russian origin, most famously borne by the novelist Fyodor Dostoevsky.
-
D.
Pyotr
Pyotr is the Russian given name of Peter Kropotkin, the influential 19th-century anarchist philosopher, geographer, and revolutionary.
-
E.
Viktor
Viktor is a powerful and ancient vampire elder from the "Underworld" film series, portrayed by actor Bill Nighy.
- 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_69aed95d315881908cbf1bf4a7215fbf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeecf17ef4819083db0a22e24d5b89 |
completed | March 9, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be6f845ce48190a5feae21980530d6 |
completed | March 21, 2026, 10:14 a.m. |
Created at: March 9, 2026, 3:21 p.m.