Triple

T28528005
Position Surface form Disambiguated ID Type / Status
Subject Clytia E721960 entity
Predicate countryOfCitizenship P2 FINISHED
Object Kingdom of Sipylus
The Kingdom of Sipylus was a mythological ancient realm in Greek legend, often associated with early Anatolian dynasties and figures such as Tantalus and his family.
E1824028 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: Kingdom of Sipylus | Statement: [Clytia, countryOfCitizenship, Kingdom of Sipylus]
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: Kingdom of Sipylus
Triple: [Clytia, countryOfCitizenship, Kingdom of Sipylus]
Generated description
The Kingdom of Sipylus was a mythological ancient realm in Greek legend, often associated with early Anatolian dynasties and figures such as Tantalus and his family.

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_69f01a5d7ec88190ada2d5be7c06c35d completed April 28, 2026, 2:24 a.m.
NER Named-entity recognition batch_69f64fd3436881909a1b7b23c22b037b completed May 2, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1cb6dc8a308190ac347b38d37757a0 completed May 31, 2026, 10:31 p.m.
NEDg Description generation batch_6a1cb917670881909255ddf24986eddc completed May 31, 2026, 10:41 p.m.
NED2 Entity disambiguation (via description) batch_6a1cb980717c81908570a4855b117ffe completed May 31, 2026, 10:43 p.m.
Created at: April 28, 2026, 3:26 a.m.