Triple

T19438875
Position Surface form Disambiguated ID Type / Status
Subject San Miguel, Manila E486296 entity
Predicate hasBarangay P29835 FINISHED
Object Barangay 733
Barangay 733 is a small local administrative unit within the San Miguel district of Manila in the Philippines.
E1405078 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: Barangay 733 | Statement: [San Miguel, Manila, hasBarangay, Barangay 733]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barangay 733
Context triple: [San Miguel, Manila, hasBarangay, Barangay 733]
  • A. Barangay 730
    Barangay 730 is a small local administrative unit within the San Miguel district of Manila in the Philippines.
  • B. Barangay 732
    Barangay 732 is a small local administrative unit within the San Miguel district of Manila in the Philippines.
  • C. Barangay 723
    Barangay 723 is a small local administrative unit within the district of San Miguel in Manila, Philippines.
  • D. Barangay 703
    Barangay 703 is a local administrative unit within the district of San Miguel in Manila, Philippines.
  • E. Barangay 673
    Barangay 673 is a local administrative unit within the San Miguel district of Manila in the Philippines.
  • 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: Barangay 733
Triple: [San Miguel, Manila, hasBarangay, Barangay 733]
Generated description
Barangay 733 is a small local administrative unit within the San Miguel district of Manila in the Philippines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Barangay 733
Target entity description: Barangay 733 is a small local administrative unit within the San Miguel district of Manila in the Philippines.
  • A. Barangay 730
    Barangay 730 is a small local administrative unit within the San Miguel district of Manila in the Philippines.
  • B. Barangay 732
    Barangay 732 is a small local administrative unit within the San Miguel district of Manila in the Philippines.
  • C. Barangay 723
    Barangay 723 is a small local administrative unit within the district of San Miguel in Manila, Philippines.
  • D. Barangay 703
    Barangay 703 is a local administrative unit within the district of San Miguel in Manila, Philippines.
  • E. Barangay 673
    Barangay 673 is a local administrative unit within the San Miguel district of Manila in the Philippines.
  • 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_69d8e8d7ad488190a3373045029b0f3b completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e633637ea48190bfa36b0b0a2762bc completed April 20, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0804e432988190a8be2ee0be5b3584 completed May 16, 2026, 5:47 a.m.
NEDg Description generation batch_6a0805b60dbc81908c82f9410f290e19 completed May 16, 2026, 5:50 a.m.
NED2 Entity disambiguation (via description) batch_6a080679b3e08190aba3254891e739ff completed May 16, 2026, 5:54 a.m.
Created at: April 10, 2026, 1:38 p.m.