Triple

T36418796
Position Surface form Disambiguated ID Type / Status
Subject Kid Elberfeld E897090 entity
Predicate nickname P55 FINISHED
Object The Tabasco Kid
The Tabasco Kid was the fiery-tempered, hard-nosed early 20th-century Major League Baseball shortstop Kid Elberfeld, known for his aggressive play and frequent clashes with umpires.
E2184118 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: The Tabasco Kid | Statement: [Kid Elberfeld, nickname, The Tabasco Kid]
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: The Tabasco Kid
Triple: [Kid Elberfeld, nickname, The Tabasco Kid]
Generated description
The Tabasco Kid was the fiery-tempered, hard-nosed early 20th-century Major League Baseball shortstop Kid Elberfeld, known for his aggressive play and frequent clashes with umpires.

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_69f76e54ce408190849acc3f7758937c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd47bda48190bb4634ea8b6baec2 completed May 3, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39c40a39388190a32abdd4bdbeaecd completed June 22, 2026, 11:23 p.m.
NEDg Description generation batch_6a39c678b4b88190b0b868ed36464004 completed June 22, 2026, 11:34 p.m.
NED2 Entity disambiguation (via description) batch_6a39c81758b48190870d473549b02784 completed June 22, 2026, 11:41 p.m.
Created at: May 3, 2026, 4:10 p.m.