Triple
T4182281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Petersburg Oblast |
E88221
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Luga |
E201599
|
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: Luga | Statement: [Saint Petersburg Oblast, contains, Luga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luga Context triple: [Saint Petersburg Oblast, contains, Luga]
-
A.
Luga
chosen
Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
-
B.
Lida
Lida is a historic city in present-day western Belarus, known for its medieval castle and former role as a regional center in the Grand Duchy of Lithuania.
-
C.
Liluah
Liluah is a suburban locality in the Howrah district of West Bengal, India, known for its residential areas and railway facilities near Kolkata.
-
D.
Goris
Goris is a town in southern Armenia known for its historic stone houses, surrounding cave dwellings, and role as a regional cultural and transportation hub.
-
E.
Laja
Laja is a small Chilean city in the Biobío Region, known for its riverside setting and proximity to the Biobío River.
- 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_69aed9477e8c81908bcb862d2db55b1d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0305e2e88190a51f176f8534f1f9 |
completed | March 9, 2026, 5:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b589fbcc5881908f245bb377082dcc |
completed | March 14, 2026, 4:16 p.m. |
Created at: March 9, 2026, 3:45 p.m.