Triple

T26392660
Position Surface form Disambiguated ID Type / Status
Subject Le Dernier Loup E663459 entity
Predicate hasAnimalTrainer P76395 FINISHED
Object Andrew Simpson
Andrew Simpson is a professional animal trainer known for working with wolves and other wildlife on major film productions.
 E1733460 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: Andrew Simpson | Statement: [Le Dernier Loup, hasAnimalTrainer, Andrew Simpson]
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: Andrew Simpson
Triple: [Le Dernier Loup, hasAnimalTrainer, Andrew Simpson]
Generated description
Andrew Simpson is a professional animal trainer known for working with wolves and other wildlife on major film productions.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasAnimalTrainer
Context triple: [Le Dernier Loup, hasAnimalTrainer, Andrew Simpson]
  • A. hasAnimalTrainerInvolved chosen
    Indicates that an animal trainer is involved in or associated with the action, event, or relationship described.
  • B. hasDogTrainingElement
    Indicates that one entity includes, involves, or is associated with a specific element or component of dog training in relation to another entity.
  • C. alsoTrains
    Indicates that an entity, in addition to its primary role or activity, is involved in training another entity.
  • D. hasAnimalActor
    Indicates that an animal serves as the acting agent or performer in the specified event or relationship.
  • E. hasAnimal
    Indicates that one entity possesses, keeps, or is associated with an animal.
  • F. None of above.

Provenance (6 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_69ee883823988190b418b111be28a44a completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f67c9fe7b48190b79b4041357edb49 completed May 2, 2026, 10:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11ec01bd3081908585388a36299898 completed May 23, 2026, 6:03 p.m.
NEDg Description generation batch_6a11ecab0ab08190847f4751971939ec completed May 23, 2026, 6:06 p.m.
NED2 Entity disambiguation (via description) batch_6a11ed32b3648190b32aa4fd2aae2643 completed May 23, 2026, 6:08 p.m.
PD Predicate disambiguation batch_69f678cc272081909e5c70f1bc7407f0 completed May 2, 2026, 10:21 p.m.
Created at: April 26, 2026, 11:27 p.m.