Triple

T4031137
Position Surface form Disambiguated ID Type / Status
Subject Tamerlan Tsarnaev E83711 entity
Predicate numberOfVictimsInMainCrime P41344 FINISHED
Object 3 killed and hundreds injured 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: 3 killed and hundreds injured | Statement: [Tamerlan Tsarnaev, numberOfVictimsInMainCrime, 3 killed and hundreds injured]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: numberOfVictimsInMainCrime
Context triple: [Tamerlan Tsarnaev, numberOfVictimsInMainCrime, 3 killed and hundreds injured]
  • A. mainVictims
    Indicates that the related entities are the primary or principal targets harmed or affected by an action, event, or perpetrator.
  • B. numberOfSuspectedVictims chosen
    Indicates the count of individuals believed or alleged to be victims in a particular incident, case, or context.
  • C. estimatedVictimsUnderAuthority
    Indicates that a specified authority is estimated to have a certain number of victims under its control, influence, or jurisdiction.
  • D. notableVictim
    Indicates that the subject is a person or entity who is notably recognized as a victim of the object (such as an event, crime, or harmful action).
  • E. numberOfPerpetrators
    Indicates the count of distinct individuals who carried out or participated in a particular act, event, or offense.
  • 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_69aed92e29ac819080f7a98b594fec05 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb0dbb8481909ff2ee49dadcd1dc completed March 9, 2026, 4:53 p.m.
PD Predicate disambiguation batch_69aef8fe440c819093a7fa22c4ff3f1a completed March 9, 2026, 4:44 p.m.
Created at: March 9, 2026, 3:36 p.m.