Triple

T25194160
Position Surface form Disambiguated ID Type / Status
Subject Consumed E630956 entity
Predicate hasContinuityWithEpisode P162083 FINISHED
Object Slabtown
Slabtown is an episode of the television series "The Walking Dead," known for focusing on Beth Greene's experiences in a hospital-run community in post-apocalyptic Atlanta.
 E1667292 NE FINISHED

How this triple was built (3 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: Slabtown | Statement: [Consumed, hasContinuityWithEpisode, Slabtown]
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: Slabtown
Triple: [Consumed, hasContinuityWithEpisode, Slabtown]
Generated description
Slabtown is an episode of the television series "The Walking Dead," known for focusing on Beth Greene's experiences in a hospital-run community in post-apocalyptic Atlanta.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasContinuityWithEpisode
Context triple: [Consumed, hasContinuityWithEpisode, Slabtown]
  • A. followsEpisode
    Indicates that one episode occurs directly after another in a sequence or series.
  • B. seriesContinuity chosen
    Indicates that one work, episode, or installment maintains narrative or canonical continuity with another within the same series.
  • C. associatedEpisode
    Indicates that one entity is linked or connected to a particular episode as its related or relevant installment.
  • D. hasEpisode
    Indicates that something, typically a series or program, includes a specific episode as one of its constituent parts.
  • E. intendedEpisodes
    Indicates that one entity is planned or designated to appear in, be used for, or be associated with specific episodes of another entity (such as a series or program).
  • F. None of above.

Provenance (6 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_69e75a8a6d088190ba1e82a4345225e7 completed April 21, 2026, 11:07 a.m.
NER Named-entity recognition batch_69f7308a096081909d66a56f3c926806 completed May 3, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_6a105d26c8648190ad342e031479f049 completed May 22, 2026, 1:41 p.m.
NEDg Description generation batch_6a105df5bf44819082f76c7e8c6728b2 completed May 22, 2026, 1:45 p.m.
NED2 Entity disambiguation (via description) batch_6a105f4ef2648190a3b26415b711b171 completed May 22, 2026, 1:51 p.m.
PD Predicate disambiguation batch_69f72a00c5f081908b6539d15baf4e12 completed May 3, 2026, 10:57 a.m.
Created at: April 21, 2026, 12:45 p.m.