Triple

T37130950
Position Surface form Disambiguated ID Type / Status
Subject Resorts World Manila E919512 entity
Predicate hasHotelBrand P25109 FINISHED
Object Hilton Manila
Hilton Manila is an upscale, contemporary hotel in Metro Manila known for its modern amenities, dining options, and convenient location within the Resorts World Manila complex near Ninoy Aquino International Airport.
E2218863 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: Hilton Manila | Statement: [Resorts World Manila, hasHotelBrand, Hilton Manila]
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: Hilton Manila
Triple: [Resorts World Manila, hasHotelBrand, Hilton Manila]
Generated description
Hilton Manila is an upscale, contemporary hotel in Metro Manila known for its modern amenities, dining options, and convenient location within the Resorts World Manila complex near Ninoy Aquino International Airport.

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_69f76e9d13e48190a108f7fbf80ff375 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb303ddb548190a7931d7a42dca88a completed May 6, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4043ac2e508190914e40fe3ffa47b6 completed June 27, 2026, 9:42 p.m.
NEDg Description generation batch_6a40443a34148190b5b0848559466617 completed June 27, 2026, 9:44 p.m.
NED2 Entity disambiguation (via description) batch_6a404639e5a88190a204ac46e57a660f completed June 27, 2026, 9:52 p.m.
Created at: May 3, 2026, 4:15 p.m.