Triple

T16434423
Position Surface form Disambiguated ID Type / Status
Subject Bangla Road E399145 entity
Predicate near P350 FINISHED
Object Patong Beach E399887 NE FINISHED

How this triple was built (2 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: Patong Beach | Statement: [Bangla Road, near, Patong Beach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Patong Beach
Context triple: [Bangla Road, near, Patong Beach]
  • A. Patong Beach chosen
    Patong Beach is Phuket’s most famous resort area, known for its long sandy shoreline, vibrant nightlife, and dense concentration of hotels, bars, and restaurants.
  • B. Pattaya Beach
    Pattaya Beach is a major resort beach in Thailand known for its vibrant nightlife, water sports, and bustling seaside promenade.
  • C. Chaweng Beach
    Chaweng Beach is a popular, long stretch of white sand and clear water on Ko Samui in Thailand, known for its lively nightlife, resorts, and water activities.
  • D. Bang Saen Beach
    Bang Saen Beach is a popular seaside resort destination in eastern Thailand known for its long sandy shoreline, local seafood, and proximity to Bangkok.
  • E. Ao Nang Beach
    Ao Nang Beach is a popular tourist beach in Krabi, Thailand, known for its scenic limestone cliffs, soft sand, and role as a gateway to nearby islands.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32ba1023481909588aa6a3c677886 completed April 18, 2026, 6:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0084aa47408190abe2ffaab84cdd85 completed May 10, 2026, 1:14 p.m.
Created at: April 10, 2026, 5:10 a.m.