Triple

T30407834
Position Surface form Disambiguated ID Type / Status
Subject Charing Cross area E773527 entity
Predicate contains P35 FINISHED
Object King Charles I statue
The King Charles I statue is an equestrian monument in central London marking the historic site of Charing Cross and depicting the executed 17th-century English monarch.
E1912138 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: King Charles I statue | Statement: [Charing Cross area, contains, King Charles I statue]
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: King Charles I statue
Triple: [Charing Cross area, contains, King Charles I statue]
Generated description
The King Charles I statue is an equestrian monument in central London marking the historic site of Charing Cross and depicting the executed 17th-century English monarch.

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_69f22490b8b48190ab10c886a8d58c89 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f686204b2c8190afea8470275fd875 completed May 2, 2026, 11:17 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27895c72c881909a944eb59c90d0ec completed June 9, 2026, 3:32 a.m.
NEDg Description generation batch_6a278b337b0c8190b870deac9a0be21a completed June 9, 2026, 3:40 a.m.
NED2 Entity disambiguation (via description) batch_6a278bb7c0908190999f35c9918d8d6c completed June 9, 2026, 3:42 a.m.
Created at: April 29, 2026, 8:04 p.m.