Triple

T17417389
Position Surface form Disambiguated ID Type / Status
Subject AV1 E423521 entity
Predicate predecessor P97 FINISHED
Object Daala
Daala is an experimental next-generation video codec project developed by Xiph.Org and Mozilla that introduced many innovative compression techniques later influencing the design of AV1.
 E1267476 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: Daala | Statement: [AV1, predecessor, Daala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Daala
Context triple: [AV1, predecessor, Daala]
  • A. Doala
    Doala is the acrobatic blue koala mascot of Japan’s Chunichi Dragons baseball team, known for his comedic backflips and eccentric performances.
  • B. Dala-Koll
    Dala-Koll is a figure from Icelandic saga literature, known primarily as the father of Höskuldur Dala-Kollsson and an early chieftain in the Dalir region.
  • C. Dola
    Dola is an island located within Lake Rakshastal in western Tibet, near the sacred Mount Kailash region.
  • D. Daule
    Daule is a town and canton in coastal Ecuador known for its rice production and location within the Guayas Province.
  • E. Lalan
    Lalan was a Chinese-born French painter, composer, and dancer known for her abstract, lyrical works and her close association with the postwar Paris art scene.
  • 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: Daala
Triple: [AV1, predecessor, Daala]
Generated description
Daala is an experimental next-generation video codec project developed by Xiph.Org and Mozilla that introduced many innovative compression techniques later influencing the design of AV1.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Daala
Target entity description: Daala is an experimental next-generation video codec project developed by Xiph.Org and Mozilla that introduced many innovative compression techniques later influencing the design of AV1.
  • A. Doala
    Doala is the acrobatic blue koala mascot of Japan’s Chunichi Dragons baseball team, known for his comedic backflips and eccentric performances.
  • B. Dala-Koll
    Dala-Koll is a figure from Icelandic saga literature, known primarily as the father of Höskuldur Dala-Kollsson and an early chieftain in the Dalir region.
  • C. Dola
    Dola is an island located within Lake Rakshastal in western Tibet, near the sacred Mount Kailash region.
  • D. Daule
    Daule is a town and canton in coastal Ecuador known for its rice production and location within the Guayas Province.
  • E. Lalan
    Lalan was a Chinese-born French painter, composer, and dancer known for her abstract, lyrical works and her close association with the postwar Paris art scene.
  • 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_69d889d7d27c819088486ce3f0627fa1 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e44233c7888190a4d2aa703b206851 completed April 19, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01a802363c8190bc0c78e78ddb013f completed May 11, 2026, 9:57 a.m.
NEDg Description generation batch_6a01a898ceb48190ba3d40c898b17158 completed May 11, 2026, 9:59 a.m.
NED2 Entity disambiguation (via description) batch_6a01a9183410819083c8239e3ce38ea2 completed May 11, 2026, 10:02 a.m.
Created at: April 10, 2026, 5:46 a.m.