Triple

T34651506
Position Surface form Disambiguated ID Type / Status
Subject Saligao E889848 entity
Predicate nearestTouristBeachArea P174400 FINISHED
Object Calangute–Candolim belt
The Calangute–Candolim belt is a popular stretch of adjoining beach resorts in North Goa, India, known for its vibrant nightlife, water sports, and dense concentration of hotels, shacks, and tourist amenities.
 E2106410 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: Calangute–Candolim belt | Statement: [Saligao, nearestTouristBeachArea, Calangute–Candolim belt]
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: Calangute–Candolim belt
Triple: [Saligao, nearestTouristBeachArea, Calangute–Candolim belt]
Generated description
The Calangute–Candolim belt is a popular stretch of adjoining beach resorts in North Goa, India, known for its vibrant nightlife, water sports, and dense concentration of hotels, shacks, and tourist amenities.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: nearestTouristBeachArea
Context triple: [Saligao, nearestTouristBeachArea, Calangute–Candolim belt]
  • A. nearestMajorBeach
    Indicates the relationship where a location is associated with the closest significant or well-known beach to it.
  • B. nearestTouristDestination chosen
    Indicates that one location is the closest tourist destination to another specified location.
  • C. hasBeachNearby
    Indicates that one location is situated close enough to another location to have convenient access to a beach.
  • D. nearestCoastalTown
    Indicates that one town is the closest coastal town geographically relative to a given reference location or town.
  • E. nearbyResortArea
    Indicates that a resort area is located close to or within a short distance of a specified place or entity.
  • F. None of above.

Provenance (6 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_69f349d825c88190bfc6170ac9281260 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f75dc25fa08190b371faf36d9fb72c completed May 3, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3748f9896481908fbc8f56c38946f9 completed June 21, 2026, 2:14 a.m.
NEDg Description generation batch_6a37497c1b848190aade6d8736ae7330 completed June 21, 2026, 2:16 a.m.
NED2 Entity disambiguation (via description) batch_6a374a3c4f248190873958f2f5f5f62e completed June 21, 2026, 2:19 a.m.
PD Predicate disambiguation batch_69f758586534819083e91172f4bf5098 completed May 3, 2026, 2:14 p.m.
Created at: May 1, 2026, 2:04 a.m.