Triple
T37370704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Narva |
E927834
|
entity |
| Predicate | hasOpposingCountry |
P126018
|
FINISHED |
| Object | Tsardom of 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: Tsardom of Russia | Statement: [Battle of Narva, hasOpposingCountry, Tsardom of Russia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpposingCountry Context triple: [Battle of Narva, hasOpposingCountry, Tsardom of Russia]
-
A.
primaryOpposingCountry
Indicates that one country is the main or principal adversary or opponent of another country in a conflict, rivalry, or opposition.
-
B.
countryOfOpposition
Indicates the country in which an entity faces opposition, resistance, or adversarial activity.
-
C.
hasOpposingFaction
Indicates that one faction stands in opposition or conflict to another faction.
-
D.
archenemyOf
Indicates a relationship in which one entity is the principal or most important enemy of another, often characterized by deep, ongoing opposition or rivalry.
-
E.
confrontationCountry
chosen
Indicates a relationship where one country is in direct conflict, opposition, or hostile engagement with another country.
- 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_69f76eb820248190a5c395ca50ad002a |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd485f57dc8190820365396d041991 |
completed | May 8, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69fd47d35da081908bec8901018d186c |
completed | May 8, 2026, 2:17 a.m. |
Created at: May 3, 2026, 4:16 p.m.