Triple
T23478291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freden i Fredrikshamn |
E570329
|
entity |
| Predicate | countryWinningWar |
P152532
|
FINISHED |
| Object | Russian Empire |
—
|
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: Russian Empire | Statement: [Freden i Fredrikshamn, countryWinningWar, Russian Empire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryWinningWar Context triple: [Freden i Fredrikshamn, countryWinningWar, Russian Empire]
-
A.
countryDuringWar
Indicates that a country exists or participates as a relevant actor during a specified war or armed conflict.
-
B.
countryAtWarWith
Indicates that two countries are engaged in an active state of war or armed conflict with each other.
-
C.
countryForWhichFought
Indicates the country on whose behalf or under whose authority an entity participated in a conflict or war.
-
D.
countryDuringBattle
Indicates that a specified country was involved in or existed as a relevant participant or context during a particular battle.
-
E.
numberOfWars
Indicates the count of distinct wars associated with or involving a given entity.
- F. None of above. chosen
Provenance (4 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_69e245af8a88819084f2704f6d265a92 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a74e7e648190b89006dce7d7ce05 |
completed | April 29, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_69f0620ac3608190b36916261ea50f54 |
completed | April 28, 2026, 7:30 a.m. |
| PDg | Predicate description generation | batch_69f0bd4a0e408190ad8916faf23562d9 |
completed | April 28, 2026, 1:59 p.m. |
Created at: April 17, 2026, 6:02 p.m.