Triple

T30748890
Position Surface form Disambiguated ID Type / Status
Subject Putatan E782893 entity
Predicate locatedInMunicipalDistrict P21214 FINISHED
Object Lone district of Muntinlupa
The Lone district of Muntinlupa is the sole legislative district representing the highly urbanized city of Muntinlupa in the Philippines’ House of Representatives.
E1928715 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: Lone district of Muntinlupa | Statement: [Putatan, locatedInMunicipalDistrict, Lone district of Muntinlupa]
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: Lone district of Muntinlupa
Triple: [Putatan, locatedInMunicipalDistrict, Lone district of Muntinlupa]
Generated description
The Lone district of Muntinlupa is the sole legislative district representing the highly urbanized city of Muntinlupa in the Philippines’ House of Representatives.

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_69f224af8d8481908bea03890c5618be completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_6a00d1eccd7c81909ba26ace423b5578 completed May 10, 2026, 6:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28991effa88190a7ef40055256e4b4 completed June 9, 2026, 10:52 p.m.
NEDg Description generation batch_6a289ab8b9c881908958b0824a1990c7 completed June 9, 2026, 10:59 p.m.
NED2 Entity disambiguation (via description) batch_6a289b39ce9c8190a342e61537c2f11f completed June 9, 2026, 11:01 p.m.
Created at: April 29, 2026, 8:38 p.m.