Triple

T30699398
Position Surface form Disambiguated ID Type / Status
Subject CMLL World Trios Championship E781569 entity
Predicate firstChampionMember P121961 FINISHED
Object Pirata Morgan
Pirata Morgan is a Mexican professional wrestler known for his long career in lucha libre, his pirate-themed persona, and his success in major promotions such as CMLL and AAA.
E1926663 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: Pirata Morgan | Statement: [CMLL World Trios Championship, firstChampionMember, Pirata Morgan]
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: Pirata Morgan
Triple: [CMLL World Trios Championship, firstChampionMember, Pirata Morgan]
Generated description
Pirata Morgan is a Mexican professional wrestler known for his long career in lucha libre, his pirate-themed persona, and his success in major promotions such as CMLL and AAA.

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_69f224ab24e08190991d6edb6df58e8b completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_6a0319206f7c8190845cc1a3a6daedcb completed May 12, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28711844408190946b2d573fe6440e completed June 9, 2026, 8:01 p.m.
NEDg Description generation batch_6a287689fc648190a3ccf1b5c94a40ad completed June 9, 2026, 8:24 p.m.
NED2 Entity disambiguation (via description) batch_6a28770182548190b06963ca19108cb8 completed June 9, 2026, 8:26 p.m.
Created at: April 29, 2026, 8:34 p.m.