Triple

T23684745
Position Surface form Disambiguated ID Type / Status
Subject Shark Fights E585131 entity
Predicate featuredFighter P101800 FINISHED
Object Matt Horwich
Matt Horwich is an American mixed martial artist known for his unorthodox personality, strong grappling skills, and appearances in promotions such as the UFC, IFL, and various regional organizations.
E1617622 NE 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: Matt Horwich | Statement: [Shark Fights, featuredFighter, Matt Horwich]
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: Matt Horwich
Triple: [Shark Fights, featuredFighter, Matt Horwich]
Generated description
Matt Horwich is an American mixed martial artist known for his unorthodox personality, strong grappling skills, and appearances in promotions such as the UFC, IFL, and various regional organizations.

Provenance (5 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_69e249037ce0819088b149608e98f685 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b4fb26c88190a6776e4dfd10d54c completed April 29, 2026, 7:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f96277a188190a5d0e100de7ff933 completed May 21, 2026, 11:32 p.m.
NEDg Description generation batch_6a0f98b7da2c8190a41721b91851924f completed May 21, 2026, 11:43 p.m.
NED2 Entity disambiguation (via description) batch_6a0f995b8b8c819097985d86ef1b9c1c completed May 21, 2026, 11:46 p.m.
Created at: April 17, 2026, 6:52 p.m.