Triple

T35959382
Position Surface form Disambiguated ID Type / Status
Subject Great Storm of 1913 E1039954 entity
Predicate alsoKnownAs P39 FINISHED
Object White Hurricane
White Hurricane is the nickname for the catastrophic Great Lakes storm of November 1913, a powerful blizzard and hurricane-force wind event that caused massive shipwrecks and loss of life.
E2163898 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: White Hurricane | Statement: [Great Storm of 1913, alsoKnownAs, White Hurricane]
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: White Hurricane
Triple: [Great Storm of 1913, alsoKnownAs, White Hurricane]
Generated description
White Hurricane is the nickname for the catastrophic Great Lakes storm of November 1913, a powerful blizzard and hurricane-force wind event that caused massive shipwrecks and loss of life.

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_69f76e26b21081909fd9ffb3aff6c77a completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7abf73a2481909cb12971a0765cc4 completed May 3, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38b704e07481908bc3828b112a1c98 completed June 22, 2026, 4:16 a.m.
NEDg Description generation batch_6a38b7d8c5fc8190a7cce91a93d1b905 completed June 22, 2026, 4:19 a.m.
NED2 Entity disambiguation (via description) batch_6a38b86a90b48190810a306e1cf50744 completed June 22, 2026, 4:22 a.m.
Created at: May 3, 2026, 4:07 p.m.