Triple

T19438935
Position Surface form Disambiguated ID Type / Status
Subject San Miguel, Manila E486296 entity
Predicate hasBarangay P29835 FINISHED
Object Barangay 793
Barangay 793 is a local administrative neighborhood unit within the San Miguel district of Manila in the Philippines.
E1465663 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 793 | Statement: [San Miguel, Manila, hasBarangay, Barangay 793]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barangay 793
Context triple: [San Miguel, Manila, hasBarangay, Barangay 793]
  • A. Barangay 790
    Barangay 790 is a local administrative unit within the San Miguel district of Manila in the Philippines.
  • B. Barangay 739
    Barangay 739 is a local administrative unit within the district of San Miguel in Manila, Philippines.
  • C. Barangay 791
    Barangay 791 is a local administrative neighborhood unit within the district of San Miguel in Manila, Philippines.
  • D. Barangay 639
    Barangay 639 is a small local administrative unit within the San Miguel district of Manila in the Philippines.
  • E. Barangay 769
    Barangay 769 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 793
Triple: [San Miguel, Manila, hasBarangay, Barangay 793]
Generated description
Barangay 793 is a local administrative neighborhood 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 793
Target entity description: Barangay 793 is a local administrative neighborhood unit within the San Miguel district of Manila in the Philippines.
  • A. Barangay 790
    Barangay 790 is a local administrative unit within the San Miguel district of Manila in the Philippines.
  • B. Barangay 739
    Barangay 739 is a local administrative unit within the district of San Miguel in Manila, Philippines.
  • C. Barangay 791
    Barangay 791 is a local administrative neighborhood unit within the district of San Miguel in Manila, Philippines.
  • D. Barangay 639
    Barangay 639 is a small local administrative unit within the San Miguel district of Manila in the Philippines.
  • E. Barangay 769
    Barangay 769 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_6a095a3c0c68819087c51a0a3d7efba7 completed May 17, 2026, 6:03 a.m.
NEDg Description generation batch_6a095aefc3f4819089e89a3b495a6d37 completed May 17, 2026, 6:06 a.m.
NED2 Entity disambiguation (via description) batch_6a095b71e4c08190a41566557503b9a8 completed May 17, 2026, 6:08 a.m.
Created at: April 10, 2026, 1:38 p.m.