Triple

T25939082
Position Surface form Disambiguated ID Type / Status
Subject Nome Kingdom E653640 entity
Predicate hasCapital P204 FINISHED
Object Nome King’s underground palace
Nome King’s underground palace is the subterranean royal stronghold and treasure-filled seat of power ruled by the Nome King in L. Frank Baum’s Oz universe.
E1701241 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: Nome King’s underground palace | Statement: [Nome Kingdom, hasCapital, Nome King’s underground palace]
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: Nome King’s underground palace
Triple: [Nome Kingdom, hasCapital, Nome King’s underground palace]
Generated description
Nome King’s underground palace is the subterranean royal stronghold and treasure-filled seat of power ruled by the Nome King in L. Frank Baum’s Oz universe.

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_69e7ab3fd2f881908837305e4ba98011 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f6045b07b08190a58fd7e0acda574c completed May 2, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ece0b9488190a26ac177ecc9b7d2 completed May 22, 2026, 11:55 p.m.
NEDg Description generation batch_6a10ee7a469881908be91b7901ada3a2 completed May 23, 2026, 12:02 a.m.
NED2 Entity disambiguation (via description) batch_6a10ef6795e08190a1ba5f600628316b completed May 23, 2026, 12:05 a.m.
Created at: April 22, 2026, 8:40 a.m.