Triple

T1496090
Position Surface form Disambiguated ID Type / Status
Subject Lvov–Sandomierz Offensive E29688 entity
Predicate timeframeRelation P4137 FINISHED
Object roughly concurrent with Operation Bagration 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: roughly concurrent with Operation Bagration | Statement: [Lvov–Sandomierz Offensive, timeframeRelation, roughly concurrent with Operation Bagration]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: timeframeRelation
Context triple: [Lvov–Sandomierz Offensive, timeframeRelation, roughly concurrent with Operation Bagration]
  • A. temporalRelation chosen
    Indicates a relationship that specifies how two events or states are positioned relative to each other in time (e.g., before, after, or overlapping).
  • B. timePeriod
    Indicates the specific span or interval of time during which an event, state, or relationship occurs or is valid.
  • C. timePeriodWithin
    Indicates that one time period is entirely contained within the bounds of another time period.
  • D. timescale
    Indicates the temporal scale or duration over which a process, relationship, or effect occurs or is evaluated.
  • E. timeEquivalentOf
    Indicates that two temporal entities represent the same point in time or duration, possibly expressed in different formats or units.
  • 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_69a498dba1d8819093b46a3a8d2485f1 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c6ec70c48190a94f6e1002848eae completed March 1, 2026, 11:08 p.m.
PD Predicate disambiguation batch_69a4c48a8cf48190a6ebf8d44a608a06 completed March 1, 2026, 10:58 p.m.
Created at: March 1, 2026, 8:12 p.m.