Triple

T5922799
Position Surface form Disambiguated ID Type / Status
Subject OpenJS Foundation E131736 entity
Predicate hostsProject P2592 FINISHED
Object Dojo
Dojo is a long-standing open-source JavaScript toolkit and framework for building rich, modular web applications.
 E554825 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: Dojo | Statement: [OpenJS Foundation, hostsProject, Dojo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dojo
Context triple: [OpenJS Foundation, hostsProject, Dojo]
  • A. Kurozumikyo
    Kurozumikyo is a Shinto-derived religious movement in Japan centered on the teachings and revelations of its founder, Kurozumi Munetada.
  • B. Dogenzaka
    Dogenzaka is a lively entertainment and shopping district in Shibuya, Tokyo, known for its nightlife, restaurants, and proximity to the famous Shibuya Crossing.
  • C. Katane
    Katane is the ancient name of the city now known as Catania, located on the eastern coast of Sicily, Italy.
  • D. Asagumo
    Asagumo was a Japanese destroyer of the Imperial Japanese Navy that saw action in World War II, including participation in major Pacific naval engagements.
  • E. Ōsu
    Ōsu is a popular shopping and entertainment district in Nagoya, Japan, known for its mix of traditional temples, vintage shops, electronics stores, and street food.
  • 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: Dojo
Triple: [OpenJS Foundation, hostsProject, Dojo]
Generated description
Dojo is a long-standing open-source JavaScript toolkit and framework for building rich, modular web applications.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dojo
Target entity description: Dojo is a long-standing open-source JavaScript toolkit and framework for building rich, modular web applications.
  • A. Kurozumikyo
    Kurozumikyo is a Shinto-derived religious movement in Japan centered on the teachings and revelations of its founder, Kurozumi Munetada.
  • B. Dogenzaka
    Dogenzaka is a lively entertainment and shopping district in Shibuya, Tokyo, known for its nightlife, restaurants, and proximity to the famous Shibuya Crossing.
  • C. Katane
    Katane is the ancient name of the city now known as Catania, located on the eastern coast of Sicily, Italy.
  • D. Asagumo
    Asagumo was a Japanese destroyer of the Imperial Japanese Navy that saw action in World War II, including participation in major Pacific naval engagements.
  • E. Ōsu
    Ōsu is a popular shopping and entertainment district in Nagoya, Japan, known for its mix of traditional temples, vintage shops, electronics stores, and street food.
  • 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_69c0085a1ed08190a7e9a8b6323fd680 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03804d9808190829a418adb7864aa completed March 22, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c0483e3481908e50f8b34b11a878 completed March 23, 2026, 4:23 a.m.
NEDg Description generation batch_69c0c1442eb48190bc67c77764116b17 completed March 23, 2026, 4:27 a.m.
NED2 Entity disambiguation (via description) batch_69c0c1c31b108190af16c66f6e8a4c25 completed March 23, 2026, 4:29 a.m.
Created at: March 22, 2026, 4 p.m.