Triple

T31383954
Position Surface form Disambiguated ID Type / Status
Subject Irene K. Pennington Softball Field E800544 entity
Predicate namedAfter P63 FINISHED
Object Irene K. Pennington
Irene K. Pennington was a prominent Louisiana philanthropist and benefactor whose support for education and community institutions led to multiple facilities, including a softball field, being named in her honor.
E1966694 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: Irene K. Pennington | Statement: [Irene K. Pennington Softball Field, namedAfter, Irene K. Pennington]
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: Irene K. Pennington
Triple: [Irene K. Pennington Softball Field, namedAfter, Irene K. Pennington]
Generated description
Irene K. Pennington was a prominent Louisiana philanthropist and benefactor whose support for education and community institutions led to multiple facilities, including a softball field, being named in her honor.

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_69f224e9d7048190b0cc20f9071bd3e4 completed April 29, 2026, 3:34 p.m.
NER Named-entity recognition batch_69f69ff3949481909cc00ff83c1ff6ff completed May 3, 2026, 1:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b2d69b858819095cd7285d18245f2 completed June 11, 2026, 9:49 p.m.
NEDg Description generation batch_6a2b2fc9c4b8819090ee482e3bccb842 completed June 11, 2026, 9:59 p.m.
NED2 Entity disambiguation (via description) batch_6a2b302215308190bf1502c98e84523e completed June 11, 2026, 10:01 p.m.
Created at: April 29, 2026, 9:19 p.m.