Triple

T26883531
Position Surface form Disambiguated ID Type / Status
Subject Breaking Bad, Season 1, Episode 1 "Pilot" E676978 entity
Predicate originalNetwork P2594 FINISHED
Object AMC
AMC is an American cable television network known for critically acclaimed original series such as "Breaking Bad," "Mad Men," and "The Walking Dead."
E82644 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: AMC | Statement: [Breaking Bad, Season 1, Episode 1 "Pilot", originalNetwork, AMC]
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: AMC
Triple: [Breaking Bad, Season 1, Episode 1 "Pilot", originalNetwork, AMC]
Generated description
AMC is an American cable television network known for critically acclaimed original series such as "Breaking Bad," "Mad Men," and "The Walking Dead."

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_69eee9bc0c90819085608c8bdc513a57 completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61f61446081909547ecbf78cf3bfc completed May 2, 2026, 3:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1213692cb08190a608a3f4ce9982b8 completed May 23, 2026, 8:51 p.m.
NEDg Description generation batch_6a1215de625081909e5c3e7bc1be4186 completed May 23, 2026, 9:02 p.m.
NED2 Entity disambiguation (via description) batch_6a1216850b6c8190a5cfaf5dfbffe878 completed May 23, 2026, 9:05 p.m.
Created at: April 27, 2026, 5:40 a.m.