Triple

T24529414
Position Surface form Disambiguated ID Type / Status
Subject Brightline station in Orlando (near theme parks) E606759 entity
Predicate nearbyAttraction P3449 FINISHED
Object Orlando theme parks
Orlando theme parks are a major cluster of world-famous amusement and entertainment resorts, including destinations like Walt Disney World and Universal Orlando, that draw millions of visitors to Central Florida each year.
E1644379 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: Orlando theme parks | Statement: [Brightline station in Orlando (near theme parks), nearbyAttraction, Orlando theme parks]
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: Orlando theme parks
Triple: [Brightline station in Orlando (near theme parks), nearbyAttraction, Orlando theme parks]
Generated description
Orlando theme parks are a major cluster of world-famous amusement and entertainment resorts, including destinations like Walt Disney World and Universal Orlando, that draw millions of visitors to Central Florida each year.

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_69e2c4c90c848190b23c4303620dcaaf completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a87872748190b98191448507481e completed April 30, 2026, 12:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10046cecb081908642afe39e5ad8c2 completed May 22, 2026, 7:23 a.m.
NEDg Description generation batch_6a1005ee1150819092f6b15e13cc9258 completed May 22, 2026, 7:29 a.m.
NED2 Entity disambiguation (via description) batch_6a100726903c81908e4d72caeed62502 completed May 22, 2026, 7:35 a.m.
Created at: April 18, 2026, 2:25 a.m.