Triple

T14000167
Position Surface form Disambiguated ID Type / Status
Subject Maharlika Highway E336799 entity
Predicate passesThrough P225 FINISHED
Object Samar E66623 NE FINISHED

How this triple was built (2 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: Samar | Statement: [Maharlika Highway, passesThrough, Samar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Samar
Context triple: [Maharlika Highway, passesThrough, Samar]
  • A. Samar
    Samar is a surname most notably associated with Sima Samar, an Afghan human rights advocate, physician, and former minister.
  • B. Samar
    Samar is a critically acclaimed Indian film directed by Shyam Benegal that explores themes of caste, power, and social injustice in rural India.
  • C. Samar Island
    Samar Island is a large island in the Eastern Visayas region of the Philippines, known for its rugged terrain, rich biodiversity, and distinct local culture.
  • D. Pomorye
    Pomorye is a historical coastal region of northern Russia along the White Sea, traditionally inhabited by the Pomors and known for maritime trade and exploration.
  • E. Samar Province chosen
    Samar Province is a largely rural island province in the Eastern Visayas region of the Philippines, known for its rugged landscapes, caves, and strong Waray-speaking cultural heritage.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2eb81b208190a961e49a02fa4140 completed April 14, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00179824c88190aeef28a08eb1a0c9 completed May 10, 2026, 5:28 a.m.
Created at: April 9, 2026, 10:19 p.m.