Triple

T1802246
Position Surface form Disambiguated ID Type / Status
Subject Los Baños, Laguna, Philippines E39746 entity
Predicate hasBarangay P29835 FINISHED
Object Bayog
Bayog is a barangay (village-level administrative division) of the municipality of Los Baños in the province of Laguna, Philippines.
E214089 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: Bayog | Statement: [Los Baños, Laguna, Philippines, hasBarangay, Bayog]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bayog
Context triple: [Los Baños, Laguna, Philippines, hasBarangay, Bayog]
  • A. Tagbanwa
    Tagbanwa is an indigenous Philippine script historically used by the Tagbanwa people of Palawan for writing their Austronesian language.
  • B. Mahikan
    Mahikan is an alternative name for the Mahican, a Native American people historically located in the Hudson River Valley of present-day New York.
  • C. Boliqueime
    Boliqueime is a small village in Portugal’s Algarve region, known for its traditional charm and proximity to the coastal resorts near Loulé.
  • D. Namaka
    Namaka is the smaller and inner of the two known moons orbiting the dwarf planet Haumea in the Kuiper Belt.
  • E. Lunan Bay
    Lunan Bay is a scenic sandy beach and coastal area on the east coast of Scotland, known for its dunes, historic ruins, and popular walking and surfing opportunities.
  • 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: Bayog
Triple: [Los Baños, Laguna, Philippines, hasBarangay, Bayog]
Generated description
Bayog is a barangay (village-level administrative division) of the municipality of Los Baños in the province of Laguna, Philippines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bayog
Target entity description: Bayog is a barangay (village-level administrative division) of the municipality of Los Baños in the province of Laguna, Philippines.
  • A. Tagbanwa
    Tagbanwa is an indigenous Philippine script historically used by the Tagbanwa people of Palawan for writing their Austronesian language.
  • B. Mahikan
    Mahikan is an alternative name for the Mahican, a Native American people historically located in the Hudson River Valley of present-day New York.
  • C. Boliqueime
    Boliqueime is a small village in Portugal’s Algarve region, known for its traditional charm and proximity to the coastal resorts near Loulé.
  • D. Namaka
    Namaka is the smaller and inner of the two known moons orbiting the dwarf planet Haumea in the Kuiper Belt.
  • E. Lunan Bay
    Lunan Bay is a scenic sandy beach and coastal area on the east coast of Scotland, known for its dunes, historic ruins, and popular walking and surfing opportunities.
  • 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_69a88632aa588190ba3978fde0db5bbd completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abaffee0f88190aa7a42ef4a4e2bd2 completed March 7, 2026, 4:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69adead0fb988190b403f5c62cbe991a completed March 8, 2026, 9:32 p.m.
NEDg Description generation batch_69adeb503ec88190b8d0cb17bbb8f520 completed March 8, 2026, 9:34 p.m.
NED2 Entity disambiguation (via description) batch_69adef13e030819086e9e8862198d859 completed March 8, 2026, 9:50 p.m.
Created at: March 4, 2026, 7:32 p.m.