Triple

T18177372
Position Surface form Disambiguated ID Type / Status
Subject TV Parental Guidelines E435197 entity
Predicate ratingCategory P64319 FINISHED
Object TV-PG
TV-PG is a television content rating indicating that parental guidance is suggested because some material may not be suitable for younger children.
 E1311685 NE FINISHED

How this triple was built (4 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: TV-PG | Statement: [TV Parental Guidelines, ratingCategory, TV-PG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TV-PG
Context triple: [TV Parental Guidelines, ratingCategory, TV-PG]
  • A. PG
    PG is the common abbreviation for Project Gutenberg, a pioneering digital library offering free access to thousands of public-domain ebooks.
  • B. PG
    PG is the international vehicle registration code used for Podgorica, the capital city of Montenegro.
  • C. PG
    PG is the commonly used abbreviation for Gdańsk University of Technology, a major technical university in Gdańsk, Poland.
  • D. PG
    PG is the stock ticker symbol for Procter & Gamble, a major American multinational consumer goods company known for brands across household, personal care, and hygiene products.
  • E. PG
    PG is the IATA airline designator used to identify Bangkok Airways on flight schedules, tickets, and aviation systems.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: TV-PG
Triple: [TV Parental Guidelines, ratingCategory, TV-PG]
Generated description
TV-PG is a television content rating indicating that parental guidance is suggested because some material may not be suitable for younger children.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TV-PG
Target entity description: TV-PG is a television content rating indicating that parental guidance is suggested because some material may not be suitable for younger children.
  • A. PG
    PG is the common abbreviation for Project Gutenberg, a pioneering digital library offering free access to thousands of public-domain ebooks.
  • B. PG
    PG is the international vehicle registration code used for Podgorica, the capital city of Montenegro.
  • C. PG
    PG is the commonly used abbreviation for Gdańsk University of Technology, a major technical university in Gdańsk, Poland.
  • D. PG
    PG is the stock ticker symbol for Procter & Gamble, a major American multinational consumer goods company known for brands across household, personal care, and hygiene products.
  • E. PG
    PG is the IATA airline designator used to identify Bangkok Airways on flight schedules, tickets, and aviation systems.
  • F. None of above. chosen

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_69d8b90c7ec081909b4694ccecb449c6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4df5a72008190bd2e56205b995a87 completed April 19, 2026, 1:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0397fd8ab481909868d3600172b0e4 completed May 12, 2026, 9:13 p.m.
NEDg Description generation batch_6a0398fb7fb481908a32c56a798d81fd completed May 12, 2026, 9:17 p.m.
NED2 Entity disambiguation (via description) batch_6a039a2b85888190bbcae1ba9d8ba715 completed May 12, 2026, 9:22 p.m.
Created at: April 10, 2026, 10:31 a.m.