Triple

T32769527
Position Surface form Disambiguated ID Type / Status
Subject Heat (1963 film) E838007 entity
Predicate productionDifficulty P78451 FINISHED
Object extreme heat during shooting LITERAL 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: extreme heat during shooting | Statement: [Heat (1963 film), productionDifficulty, extreme heat during shooting]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: productionDifficulty
Context triple: [Heat (1963 film), productionDifficulty, extreme heat during shooting]
  • A. difficulty
    Indicates the level of challenge, complexity, or effort required to perform an action, solve a problem, or achieve a particular outcome.
  • B. difficultySource chosen
    Indicates that one entity is the cause, origin, or contributing factor to the difficulty or challenge experienced in relation to another entity or situation.
  • C. difficultyModes
    Indicates the different levels of challenge or complexity available for performing a task, activity, or process.
  • D. difficultyOption
    Indicates a relationship where a particular option specifies or represents a level of difficulty for something (e.g., a task, question, or activity).
  • E. difficultyIncreasesWith
    Indicates that the level of difficulty becomes greater as the associated factor, condition, or parameter increases.
  • F. None of above.

Provenance (3 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_69f34939857c8190aa9970c51feec1eb completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69fdfbafe32081909c62653ff4fc155c completed May 8, 2026, 3:05 p.m.
PD Predicate disambiguation batch_69fdf64db4a881908f8250e24ae3cefb completed May 8, 2026, 2:42 p.m.
Created at: May 1, 2026, 1:13 a.m.