Triple

T36675890
Position Surface form Disambiguated ID Type / Status
Subject Voltron: Legendary Defender E905540 entity
Predicate featuresVehicle P16722 FINISHED
Object Yellow Lion
Yellow Lion is one of the five robotic lion mechas in the animated series "Voltron: Legendary Defender," piloted by Hunk and forming the right leg of Voltron.
E2195283 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: Yellow Lion | Statement: [Voltron: Legendary Defender, featuresVehicle, Yellow Lion]
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: Yellow Lion
Triple: [Voltron: Legendary Defender, featuresVehicle, Yellow Lion]
Generated description
Yellow Lion is one of the five robotic lion mechas in the animated series "Voltron: Legendary Defender," piloted by Hunk and forming the right leg of Voltron.

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_69f76e7011dc819082b324f18b756a1b completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c7a311588190928d93aa1eab4d7e completed May 3, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3a381d57d481908e982f60bfb59da3 completed June 23, 2026, 7:39 a.m.
NEDg Description generation batch_6a3a38cef65c8190a4c5dafe793fcf7c completed June 23, 2026, 7:42 a.m.
NED2 Entity disambiguation (via description) batch_6a3a3a51dabc81909cf57f44ec196576 completed June 23, 2026, 7:48 a.m.
Created at: May 3, 2026, 4:12 p.m.