Triple

T37897312
Position Surface form Disambiguated ID Type / Status
Subject Kareem Campbell E945314 entity
Predicate sponsor P67 FINISHED
Object City Stars Skateboards
City Stars Skateboards is a skateboard company founded by professional skater Kareem Campbell, known for its influential presence in street skate culture and team of prominent riders.
E2248391 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: City Stars Skateboards | Statement: [Kareem Campbell, sponsor, City Stars Skateboards]
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: City Stars Skateboards
Triple: [Kareem Campbell, sponsor, City Stars Skateboards]
Generated description
City Stars Skateboards is a skateboard company founded by professional skater Kareem Campbell, known for its influential presence in street skate culture and team of prominent riders.

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_69f76ef0e8708190987c7254ed8c7abe completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbbd3bb1f88190a648fadd2175dbf5 completed May 6, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a410cc2b2d0819089452438fd41c600 completed June 28, 2026, noon
NEDg Description generation batch_6a410d70ba0c8190bdcab9e762c92884 completed June 28, 2026, 12:02 p.m.
NED2 Entity disambiguation (via description) batch_6a410e3dd828819099fc3a413bcfbeb9 completed June 28, 2026, 12:06 p.m.
Created at: May 3, 2026, 4:19 p.m.