Triple

T32224582
Position Surface form Disambiguated ID Type / Status
Subject Tilion E823159 entity
Predicate otherName P39 FINISHED
Object Steersman of the Moon
Steersman of the Moon is an epithet for Tilion, the Maia in Tolkien’s legendarium who guides the Moon across the sky.
 E1997791 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: Steersman of the Moon | Statement: [Tilion, otherName, Steersman of the Moon]
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: Steersman of the Moon
Triple: [Tilion, otherName, Steersman of the Moon]
Generated description
Steersman of the Moon is an epithet for Tilion, the Maia in Tolkien’s legendarium who guides the Moon across the sky.

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_69f3490b4f948190b99e4f999f5be25f completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bbc8c6c881908ce99e774c010ff5 completed May 3, 2026, 3:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f3ba36a288190a30af08560811e6f completed June 14, 2026, 11:39 p.m.
NEDg Description generation batch_6a2f3ce130f88190ae960723f7724e69 completed June 14, 2026, 11:44 p.m.
NED2 Entity disambiguation (via description) batch_6a2f417c081081909fdbc5dfacdf273d completed June 15, 2026, 12:04 a.m.
Created at: May 1, 2026, 12:38 a.m.