Triple

T37130561
Position Surface form Disambiguated ID Type / Status
Subject Sentosa Golf Club E919503 entity
Predicate formerCourseName P202836 FINISHED
Object Tanjong Course
Tanjong Course is a renowned championship golf course on Sentosa Island in Singapore, known for its scenic coastal layout and challenging design.
 E2214809 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: Tanjong Course | Statement: [Sentosa Golf Club, formerCourseName, Tanjong Course]
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: Tanjong Course
Triple: [Sentosa Golf Club, formerCourseName, Tanjong Course]
Generated description
Tanjong Course is a renowned championship golf course on Sentosa Island in Singapore, known for its scenic coastal layout and challenging design.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: formerCourseName
Context triple: [Sentosa Golf Club, formerCourseName, Tanjong Course]
  • A. formerCourse
    Indicates that one entity previously served as a course for another entity but no longer holds that status.
  • B. formerCourseUsedFor
    Indicates that one course previously served as preparation, credit, or a prerequisite fulfilling the role now associated with another course.
  • C. previousCourse
    Indicates that one course must be taken before another, typically as a prerequisite or earlier offering in a sequence.
  • D. courseName
    Indicates the specific name or title assigned to a course in an educational context.
  • E. formerUniversityName
    Indicates that an institution previously had a different official university name than the one it currently holds.
  • 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_69f76e9d13e48190a108f7fbf80ff375 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_6a00c3362dcc819096e49b882709fddd completed May 10, 2026, 5:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3f6a21c2d4819094c6278adb72d61e completed June 27, 2026, 6:13 a.m.
NEDg Description generation batch_6a3f6ab571688190af49b225e0aeeca6 completed June 27, 2026, 6:16 a.m.
NED2 Entity disambiguation (via description) batch_6a3ffa2256708190942bb44328d3ea0b completed June 27, 2026, 4:28 p.m.
PD Predicate disambiguation batch_6a00c2e5cdd88190a5f2d0f6a843cd56 completed May 10, 2026, 5:39 p.m.
PDg Predicate description generation batch_6a00c3355498819088253d5e5c17267f completed May 10, 2026, 5:41 p.m.
Created at: May 3, 2026, 4:15 p.m.