Triple

T7376148
Position Surface form Disambiguated ID Type / Status
Subject Alex Karpovsky E170127 entity
Predicate directed P7373 FINISHED
Object Almost in Love
Almost in Love is an independent romantic dramedy film known for its naturalistic dialogue and ensemble storytelling, directed by filmmaker and actor Alex Karpovsky.
 E659949 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: Almost in Love | Statement: [Alex Karpovsky, directed, Almost in Love]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Almost in Love
Context triple: [Alex Karpovsky, directed, Almost in Love]
  • A. So in Love
    "So in Love" is a romantic ballad by Cole Porter, best known as one of the standout songs from his 1948 musical *Kiss Me, Kate*.
  • B. In Case You’re in Love
    "In Case You’re in Love" is a 1967 pop album by the American duo Sonny & Cher, featuring their hit single "The Beat Goes On."
  • C. The Love in Me
    "The Love in Me" is a song featured on the Christian music album "Something About Faith."
  • D. A Little Bit in Love
    "A Little Bit in Love" is a romantic show tune from the 1953 Broadway musical *Wonderful Town*, with music by Leonard Bernstein and lyrics by Betty Comden and Adolph Green.
  • E. So Much in Love
    "So Much in Love" is a romantic R&B song best known as a hit single by the British boy band Take That.
  • 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: Almost in Love
Triple: [Alex Karpovsky, directed, Almost in Love]
Generated description
Almost in Love is an independent romantic dramedy film known for its naturalistic dialogue and ensemble storytelling, directed by filmmaker and actor Alex Karpovsky.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Almost in Love
Target entity description: Almost in Love is an independent romantic dramedy film known for its naturalistic dialogue and ensemble storytelling, directed by filmmaker and actor Alex Karpovsky.
  • A. So in Love
    "So in Love" is a romantic ballad by Cole Porter, best known as one of the standout songs from his 1948 musical *Kiss Me, Kate*.
  • B. In Case You’re in Love
    "In Case You’re in Love" is a 1967 pop album by the American duo Sonny & Cher, featuring their hit single "The Beat Goes On."
  • C. The Love in Me
    "The Love in Me" is a song featured on the Christian music album "Something About Faith."
  • D. A Little Bit in Love
    "A Little Bit in Love" is a romantic show tune from the 1953 Broadway musical *Wonderful Town*, with music by Leonard Bernstein and lyrics by Betty Comden and Adolph Green.
  • E. So Much in Love
    "So Much in Love" is a romantic R&B song best known as a hit single by the British boy band Take That.
  • 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_69c68a5bfaac81909ce7f001dfb70c76 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f1a8b18c8190ad1a19521eda2319 completed March 27, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c802d15a8481908e43701459607276 completed March 28, 2026, 4:33 p.m.
NEDg Description generation batch_69c803ad72308190a9640f2fb043daab completed March 28, 2026, 4:37 p.m.
NED2 Entity disambiguation (via description) batch_69c8043121988190b7c9ea0f786296c2 completed March 28, 2026, 4:39 p.m.
Created at: March 27, 2026, 3:07 p.m.