Triple

T23730238
Position Surface form Disambiguated ID Type / Status
Subject Notes of a Dirty Old Man E586390 entity
Predicate originalColumnVenue P153736 FINISHED
Object Open City
Open City was an underground newspaper of the 1960s counterculture scene in Los Angeles, known for publishing alternative journalism, literature, and columns by writers like Charles Bukowski.
 E1599946 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: Open City | Statement: [Notes of a Dirty Old Man, originalColumnVenue, Open City]
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: Open City
Triple: [Notes of a Dirty Old Man, originalColumnVenue, Open City]
Generated description
Open City was an underground newspaper of the 1960s counterculture scene in Los Angeles, known for publishing alternative journalism, literature, and columns by writers like Charles Bukowski.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: originalColumnVenue
Context triple: [Notes of a Dirty Old Man, originalColumnVenue, Open City]
  • A. startVenue
    Indicates the venue or location where an event, journey, or activity begins.
  • B. previousVenue
    Indicates that one venue was used or occupied before another in a sequence of venues.
  • C. formerVenueComponentOf
    Indicates that a venue previously functioned as a component or part of a larger venue or venue complex, but no longer holds that status.
  • D. originalPerformanceVenue
    Indicates the venue where a performance was first originally presented or premiered.
  • E. formerVenueLocation
    Indicates that a location previously served as the venue for an entity or event but no longer does so.
  • F. None of above. chosen

Provenance (7 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_69e24907dc9c8190be074c9c96a0ec2d completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b9180bf48190a6c3656ef0530463 completed April 29, 2026, 7:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f53c5aa408190a35ed8156a730f6a completed May 21, 2026, 6:49 p.m.
NEDg Description generation batch_6a0f571cb9cc8190b9af3358abcd01f9 completed May 21, 2026, 7:03 p.m.
NED2 Entity disambiguation (via description) batch_6a0f57ca769081908f3ae56eeb36bfba completed May 21, 2026, 7:06 p.m.
PD Predicate disambiguation batch_69f155e4b1148190836ede4741dcb888 completed April 29, 2026, 12:50 a.m.
PDg Predicate description generation batch_69f15b453da88190889a8d9b21727958 completed April 29, 2026, 1:13 a.m.
Created at: April 17, 2026, 7:09 p.m.