Triple
T28437877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Ula |
E715619
|
entity |
| Predicate | opponentDescriptor |
P167915
|
FINISHED |
| Object | larger Russian army |
—
|
LITERAL 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: larger Russian army | Statement: [Battle of Ula, opponentDescriptor, larger Russian army]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opponentDescriptor Context triple: [Battle of Ula, opponentDescriptor, larger Russian army]
-
A.
opponentInScenario
Indicates that one entity is an adversary or rival of another within a specific scenario, context, or situation.
-
B.
opponentState
Indicates the condition or status that an opposing party or competitor is currently in within a given context or interaction.
-
C.
opponentInCase
Indicates that two parties are on opposing sides in the same legal case or proceeding.
-
D.
associatedOpponent
Indicates that one entity is recognized or designated as an opponent or adversary associated with another entity in a given context.
-
E.
opponentCandidate
Indicates that one entity is a rival or competing candidate against another in the same contest or election.
- 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_69efd6b44550819094ae991b553d9fc3 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f66e5f7e30819094530abceabd5f43 |
completed | May 2, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66d75a8788190aa9ca2c977429045 |
completed | May 2, 2026, 9:32 p.m. |
Created at: April 28, 2026, 1:44 a.m.