Triple

T9795682
Position Surface form Disambiguated ID Type / Status
Subject The Grave E237710 entity
Predicate character P662 FINISHED
Object Sissy
Sissy is a fictional character from the horror film "The Grave," known for her involvement in the movie’s dark, suspenseful storyline.
 E822363 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: Sissy | Statement: [The Grave, character, Sissy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sissy
Context triple: [The Grave, character, Sissy]
  • A. Prissy
    Prissy is a diminutive nickname for the given name Priscilla, often used as an affectionate or informal form.
  • B. Betsy
    Betsy is a key female character in the 1976 film "Taxi Driver," known as the idealistic campaign worker who becomes the object of Travis Bickle’s fixation.
  • C. Betsy
    Betsy is a common diminutive or nickname for the given name Elizabeth.
  • D. Sissyneck
    "Sissyneck" is a funky, genre-blending track by Beck from his acclaimed 1996 album *Odelay*, known for its eclectic mix of rock, hip-hop, and country influences.
  • E. Barbara
    Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
  • 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: Sissy
Triple: [The Grave, character, Sissy]
Generated description
Sissy is a fictional character from the horror film "The Grave," known for her involvement in the movie’s dark, suspenseful storyline.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sissy
Target entity description: Sissy is a fictional character from the horror film "The Grave," known for her involvement in the movie’s dark, suspenseful storyline.
  • A. Prissy
    Prissy is a diminutive nickname for the given name Priscilla, often used as an affectionate or informal form.
  • B. Betsy
    Betsy is a key female character in the 1976 film "Taxi Driver," known as the idealistic campaign worker who becomes the object of Travis Bickle’s fixation.
  • C. Betsy
    Betsy is a common diminutive or nickname for the given name Elizabeth.
  • D. Sissyneck
    "Sissyneck" is a funky, genre-blending track by Beck from his acclaimed 1996 album *Odelay*, known for its eclectic mix of rock, hip-hop, and country influences.
  • E. Barbara
    Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
  • 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_69ca84dc04488190b9c91193976c0960 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda34916dc8190acef2ba003e56a33 completed April 1, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1c43bccfc81909b940b180fe26626 completed April 5, 2026, 2:09 a.m.
NEDg Description generation batch_69d1c5e6a2f881908666328ce72a95ed completed April 5, 2026, 2:16 a.m.
NED2 Entity disambiguation (via description) batch_69d1c68311008190b2d5b8a2fadfba69 completed April 5, 2026, 2:18 a.m.
Created at: March 30, 2026, 8:28 p.m.