Triple

T23728974
Position Surface form Disambiguated ID Type / Status
Subject Red Hot & Boom E586356 entity
Predicate heldIn P2777 FINISHED
Object Cranes Roost Park, Altamonte Springs
Cranes Roost Park in Altamonte Springs is a popular lakeside urban park and event venue known for hosting large community celebrations and concerts.
E1600567 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: Cranes Roost Park, Altamonte Springs | Statement: [Red Hot & Boom, heldIn, Cranes Roost Park, Altamonte Springs]
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: Cranes Roost Park, Altamonte Springs
Triple: [Red Hot & Boom, heldIn, Cranes Roost Park, Altamonte Springs]
Generated description
Cranes Roost Park in Altamonte Springs is a popular lakeside urban park and event venue known for hosting large community celebrations and concerts.

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_69e24907dc9c8190be074c9c96a0ec2d completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b91740ac81908ca99de0c56f6b57 completed April 29, 2026, 7:53 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f53c3dc9c8190a85075df1790d669 completed May 21, 2026, 6:49 p.m.
NEDg Description generation batch_6a0f579b03d881909aa6ea3d79a030fa completed May 21, 2026, 7:06 p.m.
NED2 Entity disambiguation (via description) batch_6a0f581d81f88190aa2299118feb3faa completed May 21, 2026, 7:08 p.m.
Created at: April 17, 2026, 7:09 p.m.