Triple

T32739093
Position Surface form Disambiguated ID Type / Status
Subject Clementine Kruczynski E837170 entity
Predicate meetsCharacterAtLocation P174749 FINISHED
Object Montauk beach
Montauk beach is a scenic Long Island shoreline famously featured as the pivotal meeting place in the film "Eternal Sunshine of the Spotless Mind."
 E2021250 NE FINISHED

How this triple was built (3 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: Montauk beach | Statement: [Clementine Kruczynski, meetsCharacterAtLocation, Montauk beach]
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: Montauk beach
Triple: [Clementine Kruczynski, meetsCharacterAtLocation, Montauk beach]
Generated description
Montauk beach is a scenic Long Island shoreline famously featured as the pivotal meeting place in the film "Eternal Sunshine of the Spotless Mind."
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: meetsCharacterAtLocation
Context triple: [Clementine Kruczynski, meetsCharacterAtLocation, Montauk beach]
  • A. isCharacterInSetting
    Indicates that a particular character appears or exists within a specified setting or environment.
  • B. hasCharacterPresence
    Indicates that a particular character appears or is present within a specified context, such as a scene, work, or medium.
  • C. meetsFictionalCharacter
    Indicates that one entity encounters or comes into contact with a fictional character.
  • D. encountersCharacter
    Indicates that one character comes into contact with or meets another character, typically within a particular situation or context.
  • E. screenCharacterBy
    Indicates a relationship where one entity evaluates or selects characters according to certain criteria or standards.
  • F. None of above. chosen

Provenance (7 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_69f34936e1748190b797e406e4e9293a completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6c906d54881909573f2d82ecd7ddd completed May 3, 2026, 4:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34a7ac1e308190b41023c04aed998d completed June 19, 2026, 2:21 a.m.
NEDg Description generation batch_6a34a88662148190b818f297a90e1a93 completed June 19, 2026, 2:25 a.m.
NED2 Entity disambiguation (via description) batch_6a34a92a11748190a6205eb616f5b475 completed June 19, 2026, 2:27 a.m.
PD Predicate disambiguation batch_69f6c3f717a88190a924d614c2c9bca3 completed May 3, 2026, 3:41 a.m.
PDg Predicate description generation batch_69f6c5fa10dc8190b2c06e4c701bd246 completed May 3, 2026, 3:50 a.m.
Created at: May 1, 2026, 1:12 a.m.