Triple

T71341
Position Surface form Disambiguated ID Type / Status
Subject Hollywood Sign E1427 entity
Predicate letterSequence P3568 FINISHED
Object W
W is one of the iconic white capital letters that make up the famous Hollywood Sign overlooking Los Angeles.
 E6886 NE FINISHED

How this triple was built (4 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: W | Statement: [Hollywood Sign, letterSequence, W]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: W
Context triple: [Hollywood Sign, letterSequence, W]
  • A. W3
    W3 is a common shorthand for the World Wide Web, the global system of interlinked hypertext documents and resources accessed via the internet.
  • B. We
    "We" is Charles Lindbergh’s autobiographical account of his historic 1927 solo nonstop flight across the Atlantic and the events surrounding it.
  • C. WY
    WY is the New York Stock Exchange ticker symbol for Weyerhaeuser Company, one of the world’s largest private owners of timberlands and a major forest products company.
  • D. WAS
    WAS is the standard three-letter abbreviation used for the Washington Commanders NFL franchise.
  • E. WAS
    WAS is the station code for Washington, D.C.’s main intercity and commuter rail hub, Union Station.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: W
Triple: [Hollywood Sign, letterSequence, W]
Generated description
W is one of the iconic white capital letters that make up the famous Hollywood Sign overlooking Los Angeles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: W
Target entity description: W is one of the iconic white capital letters that make up the famous Hollywood Sign overlooking Los Angeles.
  • A. W3
    W3 is a common shorthand for the World Wide Web, the global system of interlinked hypertext documents and resources accessed via the internet.
  • B. We
    "We" is Charles Lindbergh’s autobiographical account of his historic 1927 solo nonstop flight across the Atlantic and the events surrounding it.
  • C. WY
    WY is the New York Stock Exchange ticker symbol for Weyerhaeuser Company, one of the world’s largest private owners of timberlands and a major forest products company.
  • D. WAS
    WAS is the standard three-letter abbreviation used for the Washington Commanders NFL franchise.
  • E. WAS
    WAS is the station code for Washington, D.C.’s main intercity and commuter rail hub, Union Station.
  • F. None of above. chosen

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_69a24c06b3bc8190aa4ac89026115efc completed Feb. 28, 2026, 1:59 a.m.
NER Named-entity recognition batch_69a2567b592c8190aaf692a18fcd2f1b completed Feb. 28, 2026, 2:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69a25abaa7dc8190b65fa9d213a40790 completed Feb. 28, 2026, 3:02 a.m.
NEDg Description generation batch_69a25ba89b70819086966936d11a8dcf completed Feb. 28, 2026, 3:06 a.m.
NED2 Entity disambiguation (via description) batch_69a25c29bf708190966d4a036ae69f10 completed Feb. 28, 2026, 3:08 a.m.
Created at: Feb. 28, 2026, 2:03 a.m.