Triple

T36404164
Position Surface form Disambiguated ID Type / Status
Subject Masjid Jamek LRT station E896705 entity
Predicate locatedNear P294 FINISHED
Object Little India Masjid India
Little India Masjid India is a mosque situated in the Little India district of Kuala Lumpur, Malaysia, serving as a key religious and cultural center for the local Muslim community.
E2182745 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: Little India Masjid India | Statement: [Masjid Jamek LRT station, locatedNear, Little India Masjid India]
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: Little India Masjid India
Triple: [Masjid Jamek LRT station, locatedNear, Little India Masjid India]
Generated description
Little India Masjid India is a mosque situated in the Little India district of Kuala Lumpur, Malaysia, serving as a key religious and cultural center for the local Muslim community.

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_69f76e53b81081908d3b81860593f38a completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd17820881909fdeb97dfdfd8e18 completed May 3, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39b4442aa48190b230fac5aea822f2 completed June 22, 2026, 10:16 p.m.
NEDg Description generation batch_6a39bc2fe42c8190bb2ea46ff2f1fa91 completed June 22, 2026, 10:50 p.m.
NED2 Entity disambiguation (via description) batch_6a39bcd287c081909de3d2f8d2b3fe29 completed June 22, 2026, 10:53 p.m.
Created at: May 3, 2026, 4:10 p.m.