Triple
T190160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul |
E3700
|
entity |
| Predicate | isCognateOf |
P2527
|
FINISHED |
| Object | Pavel |
E43273
|
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: Pavel | Statement: [Paul, isCognateOf, Pavel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pavel Context triple: [Paul, isCognateOf, Pavel]
-
A.
Pavel
chosen
Pavel is a Slavic given name, equivalent to the English name Paul.
-
B.
Mikhail
Mikhail is a common Russian male given name, famously borne by Soviet leader Mikhail Gorbachev.
-
C.
Andrei
Andrei is a masculine given name commonly used in Slavic and Eastern European countries, equivalent to the English name Andrew.
-
D.
Igor Babuschkin
Igor Babuschkin is an AI researcher and engineer known for his work on large language models at organizations such as DeepMind, OpenAI, and later xAI.
-
E.
Valentin Pavlov
Valentin Pavlov was a Soviet politician and economist who briefly served as the last Prime Minister of the Soviet Union during its final months before dissolution.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a25bc834388190a93ec1ab0d5946de |
completed | Feb. 28, 2026, 3:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3d7e0801c8190aa1f1c5f8d5bc3cb |
completed | March 1, 2026, 6:08 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.