Triple

T33459921
Position Surface form Disambiguated ID Type / Status
Subject Royal Army of Oz E856882 entity
Predicate allegiance P1201 FINISHED
Object King of the Emerald City
The King of the Emerald City is the sovereign ruler of the glittering green capital of the Land of Oz, presiding over its citizens and commanding its royal institutions.
E2052281 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: King of the Emerald City | Statement: [Royal Army of Oz, allegiance, King of the Emerald City]
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: King of the Emerald City
Triple: [Royal Army of Oz, allegiance, King of the Emerald City]
Generated description
The King of the Emerald City is the sovereign ruler of the glittering green capital of the Land of Oz, presiding over its citizens and commanding its royal institutions.

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_69f3497281a08190b4705de0b5f26ba7 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e4d1da788190a2bac16ea7ddad54 completed May 3, 2026, 6:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a358169c4fc819097296992126a6319 completed June 19, 2026, 5:50 p.m.
NEDg Description generation batch_6a35857c0008819092ad90f2d9aa4bba completed June 19, 2026, 6:07 p.m.
NED2 Entity disambiguation (via description) batch_6a358a6e3500819082641146aec17075 completed June 19, 2026, 6:29 p.m.
Created at: May 1, 2026, 1:37 a.m.