Triple

T12112472
Position Surface form Disambiguated ID Type / Status
Subject PNR Metro Commuter Line E288466 entity
Predicate terminus P388 FINISHED
Object Tutuban
Tutuban is a major railway station and historic transport hub in Manila, Philippines, serving as the central terminal for several Philippine National Railways commuter services.
 E969411 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: Tutuban | Statement: [PNR Metro Commuter Line, terminus, Tutuban]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tutuban
Context triple: [PNR Metro Commuter Line, terminus, Tutuban]
  • A. Shumshu
    Shumshu is a small, strategically significant volcanic island at the northern end of the Kuril Islands chain, near the Kamchatka Peninsula.
  • B. Takamikura
    Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
  • C. Taburao
    Taburao is a village on the atoll of Abaiang in the island nation of Kiribati.
  • D. Tonekabon
    Tonekabon is a coastal city in northern Iran known for its lush landscapes, citrus orchards, and location along the southern shore of the Caspian Sea.
  • E. Gotemba
    Gotemba is a Japanese city in Shizuoka Prefecture known as a gateway to Mount Fuji and a popular base for outdoor activities and outlet shopping.
  • 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: Tutuban
Triple: [PNR Metro Commuter Line, terminus, Tutuban]
Generated description
Tutuban is a major railway station and historic transport hub in Manila, Philippines, serving as the central terminal for several Philippine National Railways commuter services.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tutuban
Target entity description: Tutuban is a major railway station and historic transport hub in Manila, Philippines, serving as the central terminal for several Philippine National Railways commuter services.
  • A. Shumshu
    Shumshu is a small, strategically significant volcanic island at the northern end of the Kuril Islands chain, near the Kamchatka Peninsula.
  • B. Takamikura
    Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
  • C. Taburao
    Taburao is a village on the atoll of Abaiang in the island nation of Kiribati.
  • D. Tonekabon
    Tonekabon is a coastal city in northern Iran known for its lush landscapes, citrus orchards, and location along the southern shore of the Caspian Sea.
  • E. Gotemba
    Gotemba is a Japanese city in Shizuoka Prefecture known as a gateway to Mount Fuji and a popular base for outdoor activities and outlet shopping.
  • 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_69d6ab4a5c448190a110d1273314b21a completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9156814148190b47d63a89fcab17c completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a75f77881908345a585a689f69f completed May 2, 2026, 2:30 p.m.
NEDg Description generation batch_69f60bda16e48190af8abc0aa8ef41f0 completed May 2, 2026, 2:36 p.m.
NED2 Entity disambiguation (via description) batch_69f60cd51d34819099927fee476958ea completed May 2, 2026, 2:40 p.m.
Created at: April 8, 2026, 9:49 p.m.