Triple

T15165429
Position Surface form Disambiguated ID Type / Status
Subject Laughing Matter E362326 entity
Predicate hasPart P35 FINISHED
Object Jennifer’s Gone
"Jennifer’s Gone" is a song featured on the album "Laughing Matter."
 E1142471 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: Jennifer’s Gone | Statement: [Laughing Matter, hasPart, Jennifer’s Gone]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jennifer’s Gone
Context triple: [Laughing Matter, hasPart, Jennifer’s Gone]
  • A. The Jennifer Morgue
    The Jennifer Morgue is a satirical science fiction spy novel by Charles Stross that blends Lovecraftian horror with a James Bond–style espionage thriller.
  • B. The Final Girls
    The Final Girls is a 2015 horror-comedy film that parodies 1980s slasher movies by trapping its characters inside a classic cult slasher film.
  • C. Gone in the Night
    Gone in the Night is a 2022 psychological thriller film starring Winona Ryder and Owen Teague that follows a woman drawn into a mysterious disappearance at a remote cabin.
  • D. Fortunately Gone
    "Fortunately Gone" is a song by the American alternative rock band The Breeders, featured on their 1990 debut album "Pod."
  • E. Before She Disappeared
    "Before She Disappeared" is a contemporary crime thriller novel by Lisa Gardner that follows an ordinary woman who obsessively searches for missing people the police have failed to find.
  • 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: Jennifer’s Gone
Triple: [Laughing Matter, hasPart, Jennifer’s Gone]
Generated description
"Jennifer’s Gone" is a song featured on the album "Laughing Matter."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jennifer’s Gone
Target entity description: "Jennifer’s Gone" is a song featured on the album "Laughing Matter."
  • A. The Jennifer Morgue
    The Jennifer Morgue is a satirical science fiction spy novel by Charles Stross that blends Lovecraftian horror with a James Bond–style espionage thriller.
  • B. The Final Girls
    The Final Girls is a 2015 horror-comedy film that parodies 1980s slasher movies by trapping its characters inside a classic cult slasher film.
  • C. Gone in the Night
    Gone in the Night is a 2022 psychological thriller film starring Winona Ryder and Owen Teague that follows a woman drawn into a mysterious disappearance at a remote cabin.
  • D. Fortunately Gone
    "Fortunately Gone" is a song by the American alternative rock band The Breeders, featured on their 1990 debut album "Pod."
  • E. Before She Disappeared
    "Before She Disappeared" is a contemporary crime thriller novel by Lisa Gardner that follows an ordinary woman who obsessively searches for missing people the police have failed to find.
  • 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_69d85a087b7c81908baa94a53dac8d68 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0064c6244819085daf8e1eafdf3f2 completed April 15, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec885d68c8190999529b69bc34fec completed May 9, 2026, 5:39 a.m.
NEDg Description generation batch_69fec93109c08190a3499e4520e31604 completed May 9, 2026, 5:42 a.m.
NED2 Entity disambiguation (via description) batch_69fecc6fa8f88190aa6956e6e2b1f8ab completed May 9, 2026, 5:55 a.m.
Created at: April 10, 2026, 3:08 a.m.