Triple

T24887738
Position Surface form Disambiguated ID Type / Status
Subject Los Angeles Dons E622903 entity
Predicate foundedBy P104 FINISHED
Object Benjamin F. Lindheimer
Benjamin F. Lindheimer was an American businessman and sports executive best known for his ownership and development of major professional sports franchises in the mid-20th century.
E2170128 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: Benjamin F. Lindheimer | Statement: [Los Angeles Dons, foundedBy, Benjamin F. Lindheimer]
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: Benjamin F. Lindheimer
Triple: [Los Angeles Dons, foundedBy, Benjamin F. Lindheimer]
Generated description
Benjamin F. Lindheimer was an American businessman and sports executive best known for his ownership and development of major professional sports franchises in the mid-20th century.

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_69e2fac4aa848190b3446a3922cec150 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f4234172348190a4f0bf7ffede6af2 completed May 1, 2026, 3:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a38dde27c248190bcab513f78267892 completed June 22, 2026, 7:01 a.m.
NEDg Description generation batch_6a38f12eeefc8190a92bf1d3004269ac completed June 22, 2026, 8:24 a.m.
NED2 Entity disambiguation (via description) batch_6a38f35df5308190991210dda64a0083 completed June 22, 2026, 8:33 a.m.
Created at: April 18, 2026, 5:25 a.m.