Triple

T34844290
Position Surface form Disambiguated ID Type / Status
Subject Bridesburg E1004423 entity
Predicate hasFeature P182 FINISHED
Object Bridesburg Recreation Center
Bridesburg Recreation Center is a neighborhood community facility in the Bridesburg section of Philadelphia that offers recreational programs, sports, and events for local residents.
E2114734 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: Bridesburg Recreation Center | Statement: [Bridesburg, hasFeature, Bridesburg Recreation Center]
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: Bridesburg Recreation Center
Triple: [Bridesburg, hasFeature, Bridesburg Recreation Center]
Generated description
Bridesburg Recreation Center is a neighborhood community facility in the Bridesburg section of Philadelphia that offers recreational programs, sports, and events for local residents.

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_69f76db97714819099b5bed36fd64e9d completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78132b2b081909e5011cba264f1cb completed May 3, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37795059748190a95acc20f053ed0b completed June 21, 2026, 5:40 a.m.
NEDg Description generation batch_6a377a2e811c8190acdf3e170abca595 completed June 21, 2026, 5:44 a.m.
NED2 Entity disambiguation (via description) batch_6a377ac60cd88190b1ea9540346df1c9 completed June 21, 2026, 5:46 a.m.
Created at: May 3, 2026, 4 p.m.