Triple

T38240837
Position Surface form Disambiguated ID Type / Status
Subject Nymeria E1013754 entity
Predicate TVTrainer P190201 FINISHED
Object Bartosz Dombrowski
Bartosz Dombrowski is a TV trainer associated with the character Nymeria, likely providing specialized coaching or guidance for television production or performance.
 E2285726 NE FINISHED

How this triple was built (3 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: Bartosz Dombrowski | Statement: [Nymeria, TVTrainer, Bartosz Dombrowski]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bartosz Dombrowski
Triple: [Nymeria, TVTrainer, Bartosz Dombrowski]
Generated description
Bartosz Dombrowski is a TV trainer associated with the character Nymeria, likely providing specialized coaching or guidance for television production or performance.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: TVTrainer
Context triple: [Nymeria, TVTrainer, Bartosz Dombrowski]
  • A. trainingGround
    Indicates a location or context where entities engage in practice, drills, or preparation activities to develop or improve skills.
  • B. evePractice
    Indicates that an entity engages in or performs a practice, activity, or exercise event.
  • C. gameCoached
    Indicates that one entity served as the coach for another entity in the context of a specific game or match.
  • D. trainingUse
    Indicates that something is used for training purposes, such as preparing, educating, or improving the skills or performance of an entity.
  • E. trainingSystem
    Indicates a system or framework used to train, instruct, or develop skills or knowledge in a target entity.
  • F. None of above. chosen

Provenance (7 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_69f76dd72a248190a5fe18db2bd1eb15 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69fcc3321ef081908023590ba70ba0cf completed May 7, 2026, 4:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a460e5281c081909cda32b43c8f9b6d completed July 2, 2026, 7:08 a.m.
NEDg Description generation batch_6a461226718881908f3a3a2b036dac38 completed July 2, 2026, 7:24 a.m.
NED2 Entity disambiguation (via description) batch_6a4612a8097c8190ac6a31ed5d69df44 completed July 2, 2026, 7:26 a.m.
PD Predicate disambiguation batch_69fcb0fdc6e08190b05e894c59481a0d completed May 7, 2026, 3:34 p.m.
PDg Predicate description generation batch_69fcc330b4288190858b49d986160706 completed May 7, 2026, 4:52 p.m.
Created at: May 3, 2026, 4:30 p.m.