Triple

T8838559
Position Surface form Disambiguated ID Type / Status
Subject Subang Jaya E210328 entity
Predicate hasNeighbourhood P4813 FINISHED
Object SS15
SS15 is a popular commercial and residential hub in Subang Jaya, Malaysia, known for its vibrant food scene, cafes, and student population.
 E761374 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: SS15 | Statement: [Subang Jaya, hasNeighbourhood, SS15]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SS15
Context triple: [Subang Jaya, hasNeighbourhood, SS15]
  • A. SS2 Via Cassia
    SS2 Via Cassia is a major Italian state road that follows the historic Via Cassia route, connecting Rome with towns and regions to its northwest.
  • B. SL5
    SL5 is a bus rapid transit route on Boston’s MBTA Silver Line that runs between downtown and the Roxbury/Dudley Square area.
  • C. LMS Black Five
    LMS Black Five is a highly successful and versatile class of British mixed-traffic steam locomotives designed by William Stanier for widespread use across the LMS network.
  • D. S5
    S5 is a commuter rail line of the Stuttgart S-Bahn network serving the Stuttgart metropolitan area in Germany.
  • E. S5
    S5 is a line of the Berlin S-Bahn rapid transit network serving routes between central Berlin and its eastern suburbs.
  • 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: SS15
Triple: [Subang Jaya, hasNeighbourhood, SS15]
Generated description
SS15 is a popular commercial and residential hub in Subang Jaya, Malaysia, known for its vibrant food scene, cafes, and student population.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SS15
Target entity description: SS15 is a popular commercial and residential hub in Subang Jaya, Malaysia, known for its vibrant food scene, cafes, and student population.
  • A. SS2 Via Cassia
    SS2 Via Cassia is a major Italian state road that follows the historic Via Cassia route, connecting Rome with towns and regions to its northwest.
  • B. SL5
    SL5 is a bus rapid transit route on Boston’s MBTA Silver Line that runs between downtown and the Roxbury/Dudley Square area.
  • C. LMS Black Five
    LMS Black Five is a highly successful and versatile class of British mixed-traffic steam locomotives designed by William Stanier for widespread use across the LMS network.
  • D. S5
    S5 is a commuter rail line of the Stuttgart S-Bahn network serving the Stuttgart metropolitan area in Germany.
  • E. S5
    S5 is a line of the Berlin S-Bahn rapid transit network serving routes between central Berlin and its eastern suburbs.
  • 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_69ca8388549c819095fd94eadefbb007 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc606c60ac8190b2b6bd7f042c02f8 completed April 1, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf89933e8c81909672bcec70f7d5ce completed April 3, 2026, 9:34 a.m.
NEDg Description generation batch_69cf8bb6d7dc8190a91864130513fa4e completed April 3, 2026, 9:43 a.m.
NED2 Entity disambiguation (via description) batch_69cf8ca3e2788190a33fb28132944759 completed April 3, 2026, 9:47 a.m.
Created at: March 30, 2026, 6:48 p.m.