Triple

T4609924
Position Surface form Disambiguated ID Type / Status
Subject The Black Cauldron E100528 entity
Predicate character P662 FINISHED
Object Gurgi
Gurgi is a timid yet loyal, creature-like companion character from Disney’s animated fantasy film "The Black Cauldron."
 E456229 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: Gurgi | Statement: [The Black Cauldron, character, Gurgi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gurgi
Context triple: [The Black Cauldron, character, Gurgi]
  • A. Gooigi
    Gooigi is a green, goo-like doppelgänger of Luigi from the Luigi’s Mansion series, used as a playable helper character to solve puzzles and reach otherwise inaccessible areas.
  • B. Smargadus
    Smargadus was the exarch of Ravenna who commissioned the Column of Phocas in the Roman Forum in the early 7th century.
  • C. Dorohusk
    Dorohusk is a village in eastern Poland near the Ukrainian border, known as an important road and rail border crossing point between the two countries.
  • D. Bulzi
    Bulzi is a small town and comune in the province of Sassari on the Italian island of Sardinia.
  • E. Barugon
    Barugon is a giant kaiju from the Gamera film series, known for its lizard-like appearance and deadly freezing and rainbow-beam abilities.
  • 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: Gurgi
Triple: [The Black Cauldron, character, Gurgi]
Generated description
Gurgi is a timid yet loyal, creature-like companion character from Disney’s animated fantasy film "The Black Cauldron."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gurgi
Target entity description: Gurgi is a timid yet loyal, creature-like companion character from Disney’s animated fantasy film "The Black Cauldron."
  • A. Gooigi
    Gooigi is a green, goo-like doppelgänger of Luigi from the Luigi’s Mansion series, used as a playable helper character to solve puzzles and reach otherwise inaccessible areas.
  • B. Smargadus
    Smargadus was the exarch of Ravenna who commissioned the Column of Phocas in the Roman Forum in the early 7th century.
  • C. Dorohusk
    Dorohusk is a village in eastern Poland near the Ukrainian border, known as an important road and rail border crossing point between the two countries.
  • D. Bulzi
    Bulzi is a small town and comune in the province of Sassari on the Italian island of Sardinia.
  • E. Barugon
    Barugon is a giant kaiju from the Gamera film series, known for its lizard-like appearance and deadly freezing and rainbow-beam abilities.
  • 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_69bd43cce1e08190a07d53af6a9b6c24 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd59be3300819095e548b488c8f75e completed March 20, 2026, 2:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfa7e918881908743818e0645da46 completed March 21, 2026, 1:55 a.m.
NEDg Description generation batch_69bdfb6fa3fc8190b79b641025710eb1 completed March 21, 2026, 1:59 a.m.
NED2 Entity disambiguation (via description) batch_69bdfbeddd7c8190955bd3363fec4ca1 completed March 21, 2026, 2:01 a.m.
Created at: March 20, 2026, 1:12 p.m.