Triple
T26401161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panemunė, Lithuania |
E663700
|
entity |
| Predicate | oppositeSettlement |
P16703
|
FINISHED |
| Object | Sovetsk, Russia |
—
|
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: Sovetsk, Russia | Statement: [Panemunė, Lithuania, oppositeSettlement, Sovetsk, Russia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oppositeSettlement Context triple: [Panemunė, Lithuania, oppositeSettlement, Sovetsk, Russia]
-
A.
otherSettlement
Indicates that one settlement is another, different settlement distinct from the primary or reference settlement.
-
B.
oppositeBankCity
chosen
Indicates that one city is located on the opposite bank of a river from another city.
-
C.
oppositeTownCountry
Indicates that two locations are situated in opposing or contrasting town and country settings, such that one is urban while the other is rural.
-
D.
isSettlementOf
Indicates that one entity is a settlement (such as a town, village, or city) that belongs to, is located within, or is administratively part of another entity.
-
E.
oppositeCityCountry
Indicates that a city and a country are located on opposite sides of the world or in geographically opposing regions relative to each other.
- F. None of above.
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_69ee883823988190b418b111be28a44a |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f66c5c13808190887180099745673b |
completed | May 2, 2026, 9:27 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 26, 2026, 11:32 p.m.