Triple

T36199367
Position Surface form Disambiguated ID Type / Status
Subject José Aldo E1047215 entity
Predicate titleHeld P7034 FINISHED
Object WEC Featherweight Champion
The WEC Featherweight Champion was the title awarded to the top 145-pound mixed martial artist in World Extreme Cagefighting, a premier MMA promotion later merged into the UFC.
E2173439 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: WEC Featherweight Champion | Statement: [José Aldo, titleHeld, WEC Featherweight Champion]
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: WEC Featherweight Champion
Triple: [José Aldo, titleHeld, WEC Featherweight Champion]
Generated description
The WEC Featherweight Champion was the title awarded to the top 145-pound mixed martial artist in World Extreme Cagefighting, a premier MMA promotion later merged into the UFC.

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_69f76e414bdc8190996f15a544220a3d completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b534d7b081909a0a382d3a52a230 completed May 3, 2026, 8:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39341b50048190b4a595da536fa1de completed June 22, 2026, 1:09 p.m.
NEDg Description generation batch_6a393551ea208190a075eb301aa99bc7 completed June 22, 2026, 1:14 p.m.
NED2 Entity disambiguation (via description) batch_6a3935ed3c3c8190bf17fe2eb6eb45d4 completed June 22, 2026, 1:17 p.m.
Created at: May 3, 2026, 4:08 p.m.