Triple

T1782128
Position Surface form Disambiguated ID Type / Status
Subject Revenge E39311 entity
Predicate composer P1361 FINISHED
Object iZLER
iZLER is a film and television composer best known for scoring the ABC drama series "Revenge."
E199991 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: iZLER | Statement: [Revenge, composer, iZLER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: iZLER
Context triple: [Revenge, composer, iZLER]
  • A. IXZ
    IXZ is the IATA airport code for Veer Savarkar International Airport serving Port Blair in the Andaman and Nicobar Islands, India.
  • B. ZUEL
    ZUEL is a prominent Chinese university specializing in economics, law, and related social sciences, located in Wuhan, Hubei Province.
  • C. Litovel
    Litovel is a historic town in the Olomouc Region of the Czech Republic, known for its traditional architecture and local brewery.
  • D. Zierer
    Zierer is a German amusement ride manufacturer known for producing family-friendly roller coasters and classic flat rides for theme parks worldwide.
  • E. KZ
    KZ is the two-letter ISO 3166-1 alpha-2 country code assigned to Kazakhstan for international standardization and identification.
  • 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: iZLER
Triple: [Revenge, composer, iZLER]
Generated description
iZLER is a film and television composer best known for scoring the ABC drama series "Revenge."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: iZLER
Target entity description: iZLER is a film and television composer best known for scoring the ABC drama series "Revenge."
  • A. IXZ
    IXZ is the IATA airport code for Veer Savarkar International Airport serving Port Blair in the Andaman and Nicobar Islands, India.
  • B. ZUEL
    ZUEL is a prominent Chinese university specializing in economics, law, and related social sciences, located in Wuhan, Hubei Province.
  • C. Litovel
    Litovel is a historic town in the Olomouc Region of the Czech Republic, known for its traditional architecture and local brewery.
  • D. Zierer
    Zierer is a German amusement ride manufacturer known for producing family-friendly roller coasters and classic flat rides for theme parks worldwide.
  • E. KZ
    KZ is the two-letter ISO 3166-1 alpha-2 country code assigned to Kazakhstan for international standardization and identification.
  • 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_69a88630519c8190a17addd83c4a3ef4 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64e34fe881908aa75f2b4141b87b completed March 6, 2026, 5:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada99f52a08190854109d152c22be0 completed March 8, 2026, 4:53 p.m.
NEDg Description generation batch_69adab04b5688190afb3418e9b9da845 completed March 8, 2026, 4:59 p.m.
NED2 Entity disambiguation (via description) batch_69adaeaf81e881908f99f5d948e3557b completed March 8, 2026, 5:15 p.m.
Created at: March 4, 2026, 7:31 p.m.