Triple
T5021303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bruno Pontecorvo |
E112854
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object | Dubna |
E264944
|
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: Dubna | Statement: [Bruno Pontecorvo, placeOfDeath, Dubna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dubna Context triple: [Bruno Pontecorvo, placeOfDeath, Dubna]
-
A.
Dubna
chosen
Dubna is a Russian town in the Moscow Oblast best known as a major center for nuclear research and home to the Joint Institute for Nuclear Research.
-
B.
Obninsk
Obninsk is a Russian city best known as the site of the world’s first grid-connected nuclear power plant and an important center for nuclear and scientific research.
-
C.
Podolsk
Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
-
D.
Kolpino
Kolpino is a town in the Kolpinsky District of Saint Petersburg, Russia, known as an industrial suburb with significant metallurgical and manufacturing enterprises.
-
E.
Priozersk
Priozersk is a small town in northwestern Russia known for its historic fortress Korela and its location on the shores of Lake Ladoga.
- 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_69bd4435c2f48190be593158cbfcf8a3 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd736399ac8190aa38efc4b4edc6a2 |
completed | March 20, 2026, 4:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be927f4ad0819096826f6cb141c90b |
completed | March 21, 2026, 12:43 p.m. |
Created at: March 20, 2026, 1:36 p.m.