Triple

T19439074
Position Surface form Disambiguated ID Type / Status
Subject San Miguel, Manila E486296 entity
Predicate hasBarangay P29835 FINISHED
Object Barangay 932
Barangay 932 is a local administrative unit within the San Miguel district of Manila in the Philippines.
E1383056 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 932 | Statement: [San Miguel, Manila, hasBarangay, Barangay 932]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barangay 932
Context triple: [San Miguel, Manila, hasBarangay, Barangay 932]
  • A. Barangay 930
    Barangay 930 is a local administrative unit within the San Miguel district of Manila in the Philippines.
  • B. Barangay 931
    Barangay 931 is a local administrative unit within the district of San Miguel in Manila, Philippines.
  • C. Barangay 639
    Barangay 639 is a small local administrative unit within the San Miguel district of Manila in the Philippines.
  • D. Barangay 723
    Barangay 723 is a small local administrative unit within the district of San Miguel in Manila, Philippines.
  • E. Barangay 913
    Barangay 913 is a local administrative unit within the district of San Miguel in Manila, 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 932
Triple: [San Miguel, Manila, hasBarangay, Barangay 932]
Generated description
Barangay 932 is a 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 932
Target entity description: Barangay 932 is a local administrative unit within the San Miguel district of Manila in the Philippines.
  • A. Barangay 930
    Barangay 930 is a local administrative unit within the San Miguel district of Manila in the Philippines.
  • B. Barangay 931
    Barangay 931 is a local administrative unit within the district of San Miguel in Manila, Philippines.
  • C. Barangay 639
    Barangay 639 is a small local administrative unit within the San Miguel district of Manila in the Philippines.
  • D. Barangay 723
    Barangay 723 is a small local administrative unit within the district of San Miguel in Manila, Philippines.
  • E. Barangay 913
    Barangay 913 is a local administrative unit within the district of San Miguel in Manila, 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_6a07576b51e08190b70519021918b280 completed May 15, 2026, 5:27 p.m.
NEDg Description generation batch_6a07588550588190963ebb3c742d4d3f completed May 15, 2026, 5:31 p.m.
NED2 Entity disambiguation (via description) batch_6a07592c42488190b140e501dd9d4ae1 completed May 15, 2026, 5:34 p.m.
Created at: April 10, 2026, 1:38 p.m.