Triple

T36557597
Position Surface form Disambiguated ID Type / Status
Subject the South E901736 entity
Predicate contains P35 FINISHED
Object Harad Road
Harad Road is a major fictional roadway in J.R.R. Tolkien’s Middle-earth that runs through the southern lands toward the realm of Harad.
E2189771 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: Harad Road | Statement: [the South, contains, Harad Road]
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: Harad Road
Triple: [the South, contains, Harad Road]
Generated description
Harad Road is a major fictional roadway in J.R.R. Tolkien’s Middle-earth that runs through the southern lands toward the realm of Harad.

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_69f7c278cc448190a432cbde353699da completed May 3, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39f909c9248190929f35fba435153f completed June 23, 2026, 3:10 a.m.
NEDg Description generation batch_6a39f9a93c988190a41594e7acf6abe9 completed June 23, 2026, 3:12 a.m.
NED2 Entity disambiguation (via description) batch_6a39fa5a823c8190ba039d94ce629a6c completed June 23, 2026, 3:15 a.m.
Created at: May 3, 2026, 4:11 p.m.