Triple

T33917307
Position Surface form Disambiguated ID Type / Status
Subject Dead of Summer E869495 entity
Predicate relatedWork P37 FINISHED
Object Once Upon a Time
Once Upon a Time is a fantasy drama television series that intertwines classic fairy-tale characters and modern-day storytelling in the fictional town of Storybrooke.
 E1687087 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: Once Upon a Time | Statement: [Dead of Summer, relatedWork, Once Upon a Time]
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: Once Upon a Time
Triple: [Dead of Summer, relatedWork, Once Upon a Time]
Generated description
Once Upon a Time is a fantasy drama television series that intertwines classic fairy-tale characters and modern-day storytelling in the fictional town of Storybrooke.

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_69f3499869bc8190b6c33a81686af226 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f701b6bc1c8190b7a64003e266c248 completed May 3, 2026, 8:05 a.m.
NED1 Entity disambiguation (via context triple) batch_6a368226fe8c819099a2b332baab128a completed June 20, 2026, 12:05 p.m.
NEDg Description generation batch_6a36831f01fc8190a5e2026f6039883d completed June 20, 2026, 12:10 p.m.
NED2 Entity disambiguation (via description) batch_6a36845c22bc819083a9cbe9c3f3be9a completed June 20, 2026, 12:15 p.m.
Created at: May 1, 2026, 1:48 a.m.