Triple

T8084634
Position Surface form Disambiguated ID Type / Status
Subject Monkey Grip E188699 entity
Predicate hasCharacter P2308 FINISHED
Object Javo
Javo is a character from the game Monkey Grip, likely depicted as a distinctive figure within its cast.
 E711215 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: Javo | Statement: [Monkey Grip, hasCharacter, Javo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Javo
Context triple: [Monkey Grip, hasCharacter, Javo]
  • A. Javakade
    Javakade is a waterfront street on Amsterdam’s Java Island known for its modern residential architecture and harborside views.
  • B. Jong Java
    Jong Java was a prominent early 20th-century Javanese youth organization in the Dutch East Indies that played a key role in the rise of Indonesian nationalism.
  • C. Java (Dzau)
    Java (Dzau) is a town in South Ossetia that serves as an important regional center and transport hub in the mountainous area north of Tskhinvali.
  • D. Javan rusa
    The Javan rusa is a medium-sized deer native to Indonesia and nearby regions, known for its coarse brown coat and importance as both a game animal and a source of meat.
  • E. Jini
    Jini is a Java-based network architecture and technology from Sun Microsystems designed to enable dynamic discovery, joining, and interaction of distributed services in a network.
  • 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: Javo
Triple: [Monkey Grip, hasCharacter, Javo]
Generated description
Javo is a character from the game Monkey Grip, likely depicted as a distinctive figure within its cast.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Javo
Target entity description: Javo is a character from the game Monkey Grip, likely depicted as a distinctive figure within its cast.
  • A. Javakade
    Javakade is a waterfront street on Amsterdam’s Java Island known for its modern residential architecture and harborside views.
  • B. Jong Java
    Jong Java was a prominent early 20th-century Javanese youth organization in the Dutch East Indies that played a key role in the rise of Indonesian nationalism.
  • C. Java (Dzau)
    Java (Dzau) is a town in South Ossetia that serves as an important regional center and transport hub in the mountainous area north of Tskhinvali.
  • D. Javan rusa
    The Javan rusa is a medium-sized deer native to Indonesia and nearby regions, known for its coarse brown coat and importance as both a game animal and a source of meat.
  • E. Jini
    Jini is a Java-based network architecture and technology from Sun Microsystems designed to enable dynamic discovery, joining, and interaction of distributed services in a network.
  • 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_69ca82b662e88190b9323daab8c28a21 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb415f73808190b69db386b447062e completed March 31, 2026, 3:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc6402e41c819095442775938d4282 completed April 1, 2026, 12:17 a.m.
NEDg Description generation batch_69cc68634dc88190bc9b9e0598929d4d completed April 1, 2026, 12:35 a.m.
NED2 Entity disambiguation (via description) batch_69cc694d861c8190b504352c1fad2c36 completed April 1, 2026, 12:39 a.m.
Created at: March 30, 2026, 5:29 p.m.