Triple
T3184762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pushkin |
E66672
|
entity |
| Predicate | formerName |
P65
|
FINISHED |
| Object | Detskoye Selo |
E66671
|
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: Detskoye Selo | Statement: [Pushkin, formerName, Detskoye Selo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Detskoye Selo Context triple: [Pushkin, formerName, Detskoye Selo]
-
A.
Gatchina
Gatchina is a historic Russian town near Saint Petersburg, known for its imperial palace complex and long association with the Romanov dynasty.
-
B.
Tsarskoye Selo
chosen
Tsarskoye Selo is a former imperial residence near Saint Petersburg, Russia, famed for its opulent palaces, landscaped parks, and role as a cultural and historical center of the Russian Empire.
-
C.
Odintsovo
Odintsovo is a town in western Russia that serves as an important suburban center just outside Moscow.
-
D.
Staraya Russa
Staraya Russa is a historic town in northwestern Russia known for its medieval heritage and mineral spa resorts.
-
E.
Krasnogorsk
Krasnogorsk is a city in western Russia that serves as an important administrative and residential center just outside Moscow.
- 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_69ad8587c1bc8190a2595f2c22ee1001 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada6bfc4248190af320471688c60f0 |
completed | March 8, 2026, 4:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3b513248190a94c2f7642151515 |
completed | March 12, 2026, 5:11 p.m. |
Created at: March 8, 2026, 3:06 p.m.