Triple

T5283550
Position Surface form Disambiguated ID Type / Status
Subject Seminyak E119555 entity
Predicate hasArea P175 FINISHED
Object Petitenget
Petitenget is a trendy coastal neighborhood in Bali, Indonesia, known for its upscale beach clubs, boutique hotels, and vibrant dining scene near Seminyak.
 E508405 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: Petitenget | Statement: [Seminyak, hasArea, Petitenget]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Petitenget
Context triple: [Seminyak, hasArea, Petitenget]
  • A. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • B. Storslett
    Storslett is a small village and administrative center in Nordreisa Municipality in Troms og Finnmark county in northern Norway.
  • C. Noatun
    Noatun is the seaside home of the Norse sea god Njord, often depicted as a peaceful, ship-filled haven by the water.
  • D. Kvænangen
    Kvænangen is a fjord in northern Norway known for its dramatic coastal scenery, rich marine life, and traditional fishing communities.
  • E. Nesbyen
    Nesbyen is a small town and municipality in southeastern Norway known for its inland valley setting, historic wooden buildings, and notably warm summer temperatures.
  • 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: Petitenget
Triple: [Seminyak, hasArea, Petitenget]
Generated description
Petitenget is a trendy coastal neighborhood in Bali, Indonesia, known for its upscale beach clubs, boutique hotels, and vibrant dining scene near Seminyak.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Petitenget
Target entity description: Petitenget is a trendy coastal neighborhood in Bali, Indonesia, known for its upscale beach clubs, boutique hotels, and vibrant dining scene near Seminyak.
  • A. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • B. Storslett
    Storslett is a small village and administrative center in Nordreisa Municipality in Troms og Finnmark county in northern Norway.
  • C. Noatun
    Noatun is the seaside home of the Norse sea god Njord, often depicted as a peaceful, ship-filled haven by the water.
  • D. Kvænangen
    Kvænangen is a fjord in northern Norway known for its dramatic coastal scenery, rich marine life, and traditional fishing communities.
  • E. Nesbyen
    Nesbyen is a small town and municipality in southeastern Norway known for its inland valley setting, historic wooden buildings, and notably warm summer temperatures.
  • 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_69bd446d05a8819092ad333a3f9c8d5c completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd84c8d2bc8190840699e5a526b756 completed March 20, 2026, 5:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06e6200881908da623e8548ec051 completed March 21, 2026, 9 p.m.
NEDg Description generation batch_69bf09d1b9088190a7bf560c8d22d225 completed March 21, 2026, 9:12 p.m.
NED2 Entity disambiguation (via description) batch_69bf0a77e3b88190904c5ed6ee48ee71 completed March 21, 2026, 9:15 p.m.
Created at: March 20, 2026, 1:52 p.m.