Triple

T24311081
Position Surface form Disambiguated ID Type / Status
Subject Six Flags Great Escape E612674 entity
Predicate founder P104 FINISHED
Object Charles R. Wood
Charles R. Wood was an American entrepreneur and amusement park pioneer best known for creating and developing the theme park that became Six Flags Great Escape in upstate New York.
E2293285 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: Charles R. Wood | Statement: [Six Flags Great Escape, founder, Charles R. Wood]
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: Charles R. Wood
Triple: [Six Flags Great Escape, founder, Charles R. Wood]
Generated description
Charles R. Wood was an American entrepreneur and amusement park pioneer best known for creating and developing the theme park that became Six Flags Great Escape in upstate New York.

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_69e2d7d91bb48190bc5377d17a85fb21 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f2922a6afc8190b02cc2d185d15a45 completed April 29, 2026, 11:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7a883512bc8190b103c3761e70feea completed Aug. 11, 2026, 2:25 a.m.
NEDg Description generation batch_6a7a88abc51c8190bc8b41d5746c88b4 completed Aug. 11, 2026, 2:27 a.m.
NED2 Entity disambiguation (via description) batch_6a7a88d6ee3c8190a7e9452c304e53d8 completed Aug. 11, 2026, 2:28 a.m.
Created at: April 18, 2026, 1:37 a.m.