Triple

T29569846
Position Surface form Disambiguated ID Type / Status
Subject The Black Tent E753271 entity
Predicate mainCharacter P1183 FINISHED
Object Colonel Sir Charles Holland
Colonel Sir Charles Holland is a fictional British military officer who serves as the central protagonist in the adventure novel "The Black Tent."
E1874005 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: Colonel Sir Charles Holland | Statement: [The Black Tent, mainCharacter, Colonel Sir Charles Holland]
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: Colonel Sir Charles Holland
Triple: [The Black Tent, mainCharacter, Colonel Sir Charles Holland]
Generated description
Colonel Sir Charles Holland is a fictional British military officer who serves as the central protagonist in the adventure novel "The Black Tent."

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_69f0ef7fcb4881908a933110adb9bda1 completed April 28, 2026, 5:33 p.m.
NER Named-entity recognition batch_69f66d46180881908ff6b2ce3a27b9c0 completed May 2, 2026, 9:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a262d6aa7c88190897b007b3ede9dc5 completed June 8, 2026, 2:48 a.m.
NEDg Description generation batch_6a2631635b348190a628533ebaab1a6b completed June 8, 2026, 3:05 a.m.
NED2 Entity disambiguation (via description) batch_6a26358d611c8190904db2b471839ee3 completed June 8, 2026, 3:22 a.m.
Created at: April 28, 2026, 5:57 p.m.