Triple

T31636178
Position Surface form Disambiguated ID Type / Status
Subject Trouton’s rule E807318 entity
Predicate relatedConcept P37 FINISHED
Object Hildebrand solubility parameter
The Hildebrand solubility parameter is a numerical measure of a substance’s cohesive energy density used to predict solubility and miscibility, especially in nonpolar and slightly polar systems.
E1971515 NE 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: Hildebrand solubility parameter | Statement: [Trouton’s rule, relatedConcept, Hildebrand solubility parameter]
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: Hildebrand solubility parameter
Triple: [Trouton’s rule, relatedConcept, Hildebrand solubility parameter]
Generated description
The Hildebrand solubility parameter is a numerical measure of a substance’s cohesive energy density used to predict solubility and miscibility, especially in nonpolar and slightly polar systems.

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_69f348d892948190915f8facacb9568c completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a916d2e08190bafc01cba73b6469 completed May 3, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b79d88bf081908e461289dea714cb completed June 12, 2026, 3:15 a.m.
NEDg Description generation batch_6a2b7a6983e481908c22bc6844ca0bd2 completed June 12, 2026, 3:18 a.m.
NED2 Entity disambiguation (via description) batch_6a2b7b71012c81909354fe000b507fc9 completed June 12, 2026, 3:22 a.m.
Created at: April 30, 2026, 10:47 p.m.