Triple

T36556472
Position Surface form Disambiguated ID Type / Status
Subject King of Rohan E901710 entity
Predicate alsoKnownAs P39 FINISHED
Object King of the Mark
King of the Mark is the royal title held by the rulers of Rohan, the horse-lords of J.R.R. Tolkien’s Middle-earth.
E2189572 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 of the Mark | Statement: [King of Rohan, alsoKnownAs, King of the Mark]
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 of the Mark
Triple: [King of Rohan, alsoKnownAs, King of the Mark]
Generated description
King of the Mark is the royal title held by the rulers of Rohan, the horse-lords of J.R.R. Tolkien’s Middle-earth.

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_69f76e634e9481908c9ba1b87ab87c26 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c277a7a08190b67a7310e8616305 completed May 3, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39e6f034fc8190af0ebae6ade6f48b completed June 23, 2026, 1:52 a.m.
NEDg Description generation batch_6a39e7fe56d88190ab437b0517616a9e completed June 23, 2026, 1:57 a.m.
NED2 Entity disambiguation (via description) batch_6a39ed0fdd188190b4907f10ddafa856 completed June 23, 2026, 2:18 a.m.
Created at: May 3, 2026, 4:11 p.m.