Triple

T2370142
Position Surface form Disambiguated ID Type / Status
Subject Rizal Park E46067 entity
Predicate alsoKnownAs P39 FINISHED
Object Luneta
Luneta is the historic urban park in Manila, Philippines, renowned as a national landmark and popular public gathering place.
E261775 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: Luneta | Statement: [Rizal Park, alsoKnownAs, Luneta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luneta
Context triple: [Rizal Park, alsoKnownAs, Luneta]
  • A. Luna
    Luna was an ancient Roman town in northern Italy that served as a key urban and commercial center for the Ligurian region.
  • B. Luna
    Luna is the natural satellite of Earth, renowned for its phases, influence on tides, and prominence in human culture and mythology.
  • C. Lunan
    Lunan is a small coastal settlement in Angus, Scotland, known for its proximity to the scenic Lunan Bay beach.
  • D. Two Moon
    Two Moon was a Northern Cheyenne chief and warrior who played a prominent leadership role against U.S. forces during the Great Sioux War of 1876.
  • E. Luma
    Luma is a small, star-shaped celestial creature from the Super Mario series, known for its cute appearance and connection to Rosalina and the cosmos.
  • 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: Luneta
Triple: [Rizal Park, alsoKnownAs, Luneta]
Generated description
Luneta is the historic urban park in Manila, Philippines, renowned as a national landmark and popular public gathering place.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Luneta
Target entity description: Luneta is the historic urban park in Manila, Philippines, renowned as a national landmark and popular public gathering place.
  • A. Luna
    Luna was an ancient Roman town in northern Italy that served as a key urban and commercial center for the Ligurian region.
  • B. Luna
    Luna is the natural satellite of Earth, renowned for its phases, influence on tides, and prominence in human culture and mythology.
  • C. Lunan
    Lunan is a small coastal settlement in Angus, Scotland, known for its proximity to the scenic Lunan Bay beach.
  • D. Two Moon
    Two Moon was a Northern Cheyenne chief and warrior who played a prominent leadership role against U.S. forces during the Great Sioux War of 1876.
  • E. Luma
    Luma is a small, star-shaped celestial creature from the Super Mario series, known for its cute appearance and connection to Rosalina and the cosmos.
  • 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_69a88a145268819083e2736cb835c696 completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abc76f5aec8190867d621e6849258c completed March 7, 2026, 6:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea8a2b1448190b19179cf379993ee completed March 9, 2026, 11:01 a.m.
NEDg Description generation batch_69aeac6b13ac81909042dddef15ec924 completed March 9, 2026, 11:18 a.m.
NED2 Entity disambiguation (via description) batch_69aead16b0a881909103e26053cfad84 completed March 9, 2026, 11:20 a.m.
Created at: March 4, 2026, 7:56 p.m.