Triple

T31403519
Position Surface form Disambiguated ID Type / Status
Subject Per Bak E801061 entity
Predicate coDeveloperOf P6901 FINISHED
Object Bak–Tang–Wiesenfeld sandpile model
The Bak–Tang–Wiesenfeld sandpile model is a foundational theoretical model in physics that illustrates self-organized criticality by showing how simple local interactions can lead to complex, scale-invariant behavior such as avalanches.
 E1961044 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: Bak–Tang–Wiesenfeld sandpile model | Statement: [Per Bak, coDeveloperOf, Bak–Tang–Wiesenfeld sandpile model]
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: Bak–Tang–Wiesenfeld sandpile model
Triple: [Per Bak, coDeveloperOf, Bak–Tang–Wiesenfeld sandpile model]
Generated description
The Bak–Tang–Wiesenfeld sandpile model is a foundational theoretical model in physics that illustrates self-organized criticality by showing how simple local interactions can lead to complex, scale-invariant behavior such as avalanches.

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_69f224ea9998819086ae2e4f4f4091c8 completed April 29, 2026, 3:34 p.m.
NER Named-entity recognition batch_69f6a05ead8481909d33d428383e9c8e completed May 3, 2026, 1:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2ad24e4a6c8190a6bb300967517c40 completed June 11, 2026, 3:20 p.m.
NEDg Description generation batch_6a2ad63616b08190b9945780971434d9 completed June 11, 2026, 3:37 p.m.
NED2 Entity disambiguation (via description) batch_6a2ae55744f48190a6f5274bac8e908e completed June 11, 2026, 4:41 p.m.
Created at: April 29, 2026, 9:20 p.m.