Triple

T11581336
Position Surface form Disambiguated ID Type / Status
Subject Kapuso Mo, Jessica Soho E274631 entity
Predicate shortName P43 FINISHED
Object KMJS
KMJS is a popular Philippine television news magazine show hosted by veteran broadcast journalist Jessica Soho, known for its human-interest stories and in-depth features.
E934730 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: KMJS | Statement: [Kapuso Mo, Jessica Soho, shortName, KMJS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KMJS
Context triple: [Kapuso Mo, Jessica Soho, shortName, KMJS]
  • A. KMJ
    KMJ is the three-letter IATA airport code for Kumamoto Airport in Kumamoto Prefecture, Japan.
  • B. MKJS
    MKJS is the ICAO airport code for Sangster International Airport in Montego Bay, Jamaica.
  • C. K_J
    K_J is the standard symbol used to denote the Josephson constant, a fundamental physical constant relating voltage and frequency in superconducting Josephson junctions.
  • D. KMBS
    KMBS is the ICAO airport code for MBS International Airport, a commercial airport serving the Tri-Cities region of Michigan, USA.
  • E. JK
    JK is the widely used nickname of Juscelino Kubitschek, the former president of Brazil best known for founding Brasília and promoting rapid national development.
  • 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: KMJS
Triple: [Kapuso Mo, Jessica Soho, shortName, KMJS]
Generated description
KMJS is a popular Philippine television news magazine show hosted by veteran broadcast journalist Jessica Soho, known for its human-interest stories and in-depth features.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: KMJS
Target entity description: KMJS is a popular Philippine television news magazine show hosted by veteran broadcast journalist Jessica Soho, known for its human-interest stories and in-depth features.
  • A. KMJ
    KMJ is the three-letter IATA airport code for Kumamoto Airport in Kumamoto Prefecture, Japan.
  • B. MKJS
    MKJS is the ICAO airport code for Sangster International Airport in Montego Bay, Jamaica.
  • C. K_J
    K_J is the standard symbol used to denote the Josephson constant, a fundamental physical constant relating voltage and frequency in superconducting Josephson junctions.
  • D. KMBS
    KMBS is the ICAO airport code for MBS International Airport, a commercial airport serving the Tri-Cities region of Michigan, USA.
  • E. JK
    JK is the widely used nickname of Juscelino Kubitschek, the former president of Brazil best known for founding Brasília and promoting rapid national development.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8904c51b881909e7be84c6f3de79f completed April 10, 2026, 5:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69e7141b16d8819099002a009260a85a completed April 21, 2026, 6:07 a.m.
NEDg Description generation batch_69e720fb192881909c129f93c8b88f42 completed April 21, 2026, 7:02 a.m.
NED2 Entity disambiguation (via description) batch_69e7233efb6c81909dbf1aef080f5598 completed April 21, 2026, 7:11 a.m.
Created at: April 8, 2026, 9:38 p.m.