Triple

T18337429
Position Surface form Disambiguated ID Type / Status
Subject Secondhand Lions E439307 entity
Predicate mpaaRating P1959 FINISHED
Object PG
PG is a Motion Picture Association film rating indicating that some material may not be suitable for children and parental guidance is suggested.
 E1318129 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: PG | Statement: [Secondhand Lions, mpaaRating, PG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PG
Context triple: [Secondhand Lions, mpaaRating, 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 IATA airline designator used to identify Bangkok Airways on flight schedules, tickets, and aviation systems.
  • C. 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.
  • D. PG
    PG is the international vehicle registration code used for Podgorica, the capital city of Montenegro.
  • E. PG
    PG is the commonly used abbreviation for Gdańsk University of Technology, a major technical university in Gdańsk, Poland.
  • 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: PG
Triple: [Secondhand Lions, mpaaRating, PG]
Generated description
PG is a Motion Picture Association film rating indicating that some material may not be suitable for children and parental guidance is suggested.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PG
Target entity description: PG is a Motion Picture Association film rating indicating that some material may not be suitable for children and parental guidance is suggested.
  • A. PG
    PG is the international vehicle registration code used for Podgorica, the capital city of Montenegro.
  • B. PG
    PG is the common abbreviation for Project Gutenberg, a pioneering digital library offering free access to thousands of public-domain ebooks.
  • 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_69d8b9175fec8190af865699b4e64d8c completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50ece387881909a5da0aa4370489c completed April 19, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03c4d4bcb08190ae701be702c0c743 completed May 13, 2026, 12:24 a.m.
NEDg Description generation batch_6a03c592f7d0819082d600901da2c2f6 completed May 13, 2026, 12:28 a.m.
NED2 Entity disambiguation (via description) batch_6a03c63ec8c48190bad47d423ab2cfe7 completed May 13, 2026, 12:30 a.m.
Created at: April 10, 2026, 10:37 a.m.