Triple

T26853595
Position Surface form Disambiguated ID Type / Status
Subject Edward Kitsis E676121 entity
Predicate coCreatorOf P806 FINISHED
Object Once Upon a Time
Once Upon a Time is a fantasy drama television series that intertwines classic fairy-tale characters with modern-day settings and narratives.
 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: [Edward Kitsis, coCreatorOf, 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: [Edward Kitsis, coCreatorOf, Once Upon a Time]
Generated description
Once Upon a Time is a fantasy drama television series that intertwines classic fairy-tale characters with modern-day settings and narratives.

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_69eee9b9d7708190a15d7485709ae981 completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61b94b4a88190b24e8955029ec64e completed May 2, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a121e96446081909de2ac26d2bac098 completed May 23, 2026, 9:39 p.m.
NEDg Description generation batch_6a12204c2da88190b71d8ea3247650d3 completed May 23, 2026, 9:46 p.m.
NED2 Entity disambiguation (via description) batch_6a12210f8ae881908b5f0a9fceb7bcf7 completed May 23, 2026, 9:50 p.m.
Created at: April 27, 2026, 5:19 a.m.