Triple
T21319027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antonio Rinaldi |
E525559
|
entity |
| Predicate | placeOfActivity |
P1527
|
FINISHED |
| Object | Gatchina |
—
|
NE NERFINISHED |
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: Gatchina | Statement: [Antonio Rinaldi, placeOfActivity, Gatchina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gatchina Context triple: [Antonio Rinaldi, placeOfActivity, Gatchina]
-
A.
Gatchina
chosen
Gatchina is a historic Russian town near Saint Petersburg, known for its imperial palace complex and long association with the Romanov dynasty.
-
B.
Ivangorod
Ivangorod is a Russian border town on the Narva River, known for its medieval fortress facing the Estonian city of Narva.
-
C.
Staraya Russa
Staraya Russa is a historic town in northwestern Russia known for its medieval heritage and mineral spa resorts.
-
D.
Vsevolozhsk
Vsevolozhsk is a town in northwestern Russia that serves as an important suburban and administrative center near Saint Petersburg.
-
E.
Torzhok
Torzhok is a historic town in western Russia known for its medieval architecture, traditional goldwork embroidery, and location on the Tvertsa River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b51ad810819098c12392c8e55f6c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e77ecf12248190bb4172ad7416775e |
completed | April 21, 2026, 1:42 p.m. |
Created at: April 16, 2026, 4:38 p.m.