Triple

T11741177
Position Surface form Disambiguated ID Type / Status
Subject Dumalag E279156 entity
Predicate hasBarangay P29835 FINISHED
Object Sulangan
Sulangan is a barangay (village-level administrative division) of the municipality of Dumalag in the province of Capiz, Philippines.
E948808 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: Sulangan | Statement: [Dumalag, hasBarangay, Sulangan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sulangan
Context triple: [Dumalag, hasBarangay, Sulangan]
  • A. Sibulan
    Sibulan is a coastal municipality in the Philippine province of Negros Oriental known as a gateway to Dumaguete City and for its local airport and seaport.
  • B. Sulat
    Sulat is a coastal municipality in the province of Eastern Samar in the Philippines, known for its rural communities and Pacific shoreline.
  • C. Saguling
    Saguling is a locality in West Java, Indonesia, best known for the Saguling Dam and its surrounding reservoir on the Citarum River.
  • D. Kalamansig
    Kalamansig is a coastal municipality in the province of Sultan Kudarat in the Philippines, known for its fishing industry and diverse indigenous communities.
  • E. Giralang
    Giralang is a residential suburb in the Belconnen district of Canberra, in the Australian Capital Territory.
  • 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: Sulangan
Triple: [Dumalag, hasBarangay, Sulangan]
Generated description
Sulangan is a barangay (village-level administrative division) of the municipality of Dumalag in the province of Capiz, Philippines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sulangan
Target entity description: Sulangan is a barangay (village-level administrative division) of the municipality of Dumalag in the province of Capiz, Philippines.
  • A. Sibulan
    Sibulan is a coastal municipality in the Philippine province of Negros Oriental known as a gateway to Dumaguete City and for its local airport and seaport.
  • B. Sulat
    Sulat is a coastal municipality in the province of Eastern Samar in the Philippines, known for its rural communities and Pacific shoreline.
  • C. Saguling
    Saguling is a locality in West Java, Indonesia, best known for the Saguling Dam and its surrounding reservoir on the Citarum River.
  • D. Kalamansig
    Kalamansig is a coastal municipality in the province of Sultan Kudarat in the Philippines, known for its fishing industry and diverse indigenous communities.
  • E. Giralang
    Giralang is a residential suburb in the Belconnen district of Canberra, in the Australian Capital Territory.
  • 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_69d6aaffec6881908bead509e8621742 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4f025f88190a39280806c9d7c33 completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f1308339ac8190b579a8c1bee2a2c2 completed April 28, 2026, 10:11 p.m.
NEDg Description generation batch_69f138b5f8988190a7ff95095eafd0b1 completed April 28, 2026, 10:46 p.m.
NED2 Entity disambiguation (via description) batch_69f14e9b30a88190a054961a2f7fc80d completed April 29, 2026, 12:19 a.m.
Created at: April 8, 2026, 9:41 p.m.