Triple

T36222174
Position Surface form Disambiguated ID Type / Status
Subject Freddie Stroma E1047878 entity
Predicate appearedIn P795 FINISHED
Object Time After Time (TV series)
Time After Time is a short-lived 2017 American science fiction drama TV series that reimagines H.G. Wells pursuing Jack the Ripper through time to present-day New York City.
E2174581 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: Time After Time (TV series) | Statement: [Freddie Stroma, appearedIn, Time After Time (TV series)]
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: Time After Time (TV series)
Triple: [Freddie Stroma, appearedIn, Time After Time (TV series)]
Generated description
Time After Time is a short-lived 2017 American science fiction drama TV series that reimagines H.G. Wells pursuing Jack the Ripper through time to present-day New York City.

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_69f76e42c878819095c8d19c0267fb87 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7b5817a9081908b4a0d6184791217 completed May 3, 2026, 8:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a394d3327708190b1ddadc8e4324be3 completed June 22, 2026, 2:56 p.m.
NEDg Description generation batch_6a39501a807c81909e7e530da5052dc3 completed June 22, 2026, 3:09 p.m.
NED2 Entity disambiguation (via description) batch_6a3950a6b05481908c3370b4ed44b141 completed June 22, 2026, 3:11 p.m.
Created at: May 3, 2026, 4:09 p.m.