Triple

T4335106
Position Surface form Disambiguated ID Type / Status
Subject Cordillera Central E97443 entity
Predicate hasPeak P8205 FINISHED
Object Mount Data
Mount Data is a prominent mountain in the Cordillera Central range of the northern Philippines, known for its cool climate, pine forests, and cultural significance to indigenous communities.
 E430669 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: Mount Data | Statement: [Cordillera Central, hasPeak, Mount Data]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mount Data
Context triple: [Cordillera Central, hasPeak, Mount Data]
  • A. Datu
    Datu is a traditional title for a chieftain or local ruler in pre-colonial Philippine societies.
  • B. Data
    Data is an android Starfleet officer in Star Trek: The Next Generation, known for his quest to understand humanity and develop emotions.
  • C. Daatu
    Daatu is a Kannada novel by S. L. Bhyrappa that explores complex social and caste dynamics in Indian society.
  • D. Core Data
    Core Data is Apple’s object graph and persistence framework used in macOS and iOS apps to manage and store model layer data.
  • E. Mounted Unit
    The Mounted Unit is a specialized police division whose officers patrol on horseback to enhance crowd control, visibility, and community engagement in urban environments.
  • 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: Mount Data
Triple: [Cordillera Central, hasPeak, Mount Data]
Generated description
Mount Data is a prominent mountain in the Cordillera Central range of the northern Philippines, known for its cool climate, pine forests, and cultural significance to indigenous communities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mount Data
Target entity description: Mount Data is a prominent mountain in the Cordillera Central range of the northern Philippines, known for its cool climate, pine forests, and cultural significance to indigenous communities.
  • A. Datu
    Datu is a traditional title for a chieftain or local ruler in pre-colonial Philippine societies.
  • B. Data
    Data is an android Starfleet officer in Star Trek: The Next Generation, known for his quest to understand humanity and develop emotions.
  • C. Daatu
    Daatu is a Kannada novel by S. L. Bhyrappa that explores complex social and caste dynamics in Indian society.
  • D. Core Data
    Core Data is Apple’s object graph and persistence framework used in macOS and iOS apps to manage and store model layer data.
  • E. Mounted Unit
    The Mounted Unit is a specialized police division whose officers patrol on horseback to enhance crowd control, visibility, and community engagement in urban environments.
  • 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_69b3454662a481908fbcd0bbfaa3a0a4 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35152bfc88190ab5d53ca38f98d8a completed March 12, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d0a9967481908828ceeb76ce4cbf completed March 14, 2026, 9:18 p.m.
NEDg Description generation batch_69b5d14748108190a6f5d4aebaa83ed6 completed March 14, 2026, 9:21 p.m.
NED2 Entity disambiguation (via description) batch_69b5d1b610888190bccace493224c373 completed March 14, 2026, 9:23 p.m.
Created at: March 12, 2026, 11:14 p.m.