Triple

T26967088
Position Surface form Disambiguated ID Type / Status
Subject Gabby Hartnett E679199 entity
Predicate notableEvent P259 FINISHED
Object Homer in the Gloamin'
"Homer in the Gloamin'" is the nickname for Chicago Cubs catcher Gabby Hartnett’s famous late-inning, twilight home run in 1938 that dramatically helped clinch the National League pennant.
E1752146 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: Homer in the Gloamin' | Statement: [Gabby Hartnett, notableEvent, Homer in the Gloamin']
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: Homer in the Gloamin'
Triple: [Gabby Hartnett, notableEvent, Homer in the Gloamin']
Generated description
"Homer in the Gloamin'" is the nickname for Chicago Cubs catcher Gabby Hartnett’s famous late-inning, twilight home run in 1938 that dramatically helped clinch the National League pennant.

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_69eeeb4f3a448190b1e94b2d4776c16e completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f621210b788190ab9e910cd635f366 completed May 2, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1229a5bd7c8190990e510ce9a1997d completed May 23, 2026, 10:26 p.m.
NEDg Description generation batch_6a122a9dabb081908ed47a5d4624d9c6 completed May 23, 2026, 10:30 p.m.
NED2 Entity disambiguation (via description) batch_6a122b453e888190a195e8247f682604 completed May 23, 2026, 10:33 p.m.
Created at: April 27, 2026, 6:36 a.m.