Triple

T36546545
Position Surface form Disambiguated ID Type / Status
Subject Isle of Balar E901155 entity
Predicate hosted P2777 FINISHED
Object court of Gil-galad
The court of Gil-galad was the royal seat and gathering place of the last High King of the Noldor in Middle-earth, where he ruled and marshaled Elven resistance against Sauron.
E2188805 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: court of Gil-galad | Statement: [Isle of Balar, hosted, court of Gil-galad]
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: court of Gil-galad
Triple: [Isle of Balar, hosted, court of Gil-galad]
Generated description
The court of Gil-galad was the royal seat and gathering place of the last High King of the Noldor in Middle-earth, where he ruled and marshaled Elven resistance against Sauron.

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_69f76e61217081908b79d610fe67b013 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c25b46b881908b941b27bce7a86a completed May 3, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39e6e9d0f4819086a1633b89222140 completed June 23, 2026, 1:52 a.m.
NEDg Description generation batch_6a39e7a923308190bb61adfe9f1010d5 completed June 23, 2026, 1:55 a.m.
NED2 Entity disambiguation (via description) batch_6a39e81c61f88190b06851eee8ea6f71 completed June 23, 2026, 1:57 a.m.
Created at: May 3, 2026, 4:11 p.m.