Triple

T11166682
Position Surface form Disambiguated ID Type / Status
Subject Amala E264175 entity
Predicate hasPart P35 FINISHED
Object Morning Light
Morning Light is a song by Indian singer and actress Amala, known for its gentle, uplifting tone and melodic style.
 E908705 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: Morning Light | Statement: [Amala, hasPart, Morning Light]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Morning Light
Context triple: [Amala, hasPart, Morning Light]
  • A. Red Morning Light
    "Red Morning Light" is an energetic rock song by Kings of Leon from their debut album "Youth & Young Manhood."
  • B. Softly, as in a Morning Sunrise
    "Softly, as in a Morning Sunrise" is a popular jazz standard originating from a 1928 operetta, widely performed and recorded by numerous jazz artists.
  • C. Daylight
    Daylight is a 1996 disaster thriller film starring Sylvester Stallone, centered on a group of survivors trapped in a collapsed tunnel beneath the Hudson River.
  • D. Daylight
    "Daylight" is a song titled to evoke themes of light, hope, or emotional clarity, commonly used in pop and rock music.
  • E. Daylight
    Daylight was a famous streamlined passenger train of the Southern Pacific Railroad, celebrated for its bright orange livery and scenic daytime runs along the California coast.
  • 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: Morning Light
Triple: [Amala, hasPart, Morning Light]
Generated description
Morning Light is a song by Indian singer and actress Amala, known for its gentle, uplifting tone and melodic style.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Morning Light
Target entity description: Morning Light is a song by Indian singer and actress Amala, known for its gentle, uplifting tone and melodic style.
  • A. Red Morning Light
    "Red Morning Light" is an energetic rock song by Kings of Leon from their debut album "Youth & Young Manhood."
  • B. Softly, as in a Morning Sunrise
    "Softly, as in a Morning Sunrise" is a popular jazz standard originating from a 1928 operetta, widely performed and recorded by numerous jazz artists.
  • C. Daylight
    Daylight is a 1996 disaster thriller film starring Sylvester Stallone, centered on a group of survivors trapped in a collapsed tunnel beneath the Hudson River.
  • D. Daylight
    "Daylight" is a song titled to evoke themes of light, hope, or emotional clarity, commonly used in pop and rock music.
  • E. Daylight
    Daylight was a famous streamlined passenger train of the Southern Pacific Railroad, celebrated for its bright orange livery and scenic daytime runs along the California coast.
  • 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_69d6aa9dafac8190bd90d2c74f661aa7 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e88843cc81909e503f0921c6d297 completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69e463945e40819087c6bdbc322a6d54 completed April 19, 2026, 5:09 a.m.
NEDg Description generation batch_69e46c37efec81908aa709587c37569d completed April 19, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_69e47292cdd08190b05c4c8b09f4f918 completed April 19, 2026, 6:13 a.m.
Created at: April 8, 2026, 9:29 p.m.