Triple

T14668677
Position Surface form Disambiguated ID Type / Status
Subject 4th Marine Regiment E344447 entity
Predicate wasStationedIn P59475 FINISHED
Object Shanghai, China E5256 NE FINISHED

How this triple was built (3 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: Shanghai, China | Statement: [4th Marine Regiment, wasStationedIn, Shanghai, China]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shanghai, China
Context triple: [4th Marine Regiment, wasStationedIn, Shanghai, China]
  • A. Shanghai chosen
    Shanghai is a major global financial hub and China’s largest city, known for its modern skyline, historic waterfront, and role as a center of international business and trade.
  • B. Shanghai
    Shanghai is an unincorporated community located in Berkeley County, West Virginia, United States.
  • C. Shanghai
    Shanghai is a major Ethereum network upgrade that introduced key changes such as enabling staked ETH withdrawals and improving the protocol’s efficiency and flexibility.
  • D. Ningbo, China
    Ningbo, China is a major port city in eastern Zhejiang province known for its long maritime history and role as a key hub in regional and international trade.
  • E. Shenzhen, China
    Shenzhen, China is a major southern Chinese metropolis known for its rapid transformation into a global technology and manufacturing hub bordering Hong Kong.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: wasStationedIn
Context triple: [4th Marine Regiment, wasStationedIn, Shanghai, China]
  • A. stationedOn
    Indicates that an entity is assigned to remain at a specific location, platform, or vehicle for duty or operational purposes.
  • B. hasDutyStation
    Indicates that an entity (such as a person or position) is assigned to a specific official location where their primary work or duties are performed.
  • C. wasMilitaryHeadquartersOf
    Indicates that a place or facility served as the main command center or headquarters for a specific military force or organization.
  • D. hasStationAt
    Indicates that an entity maintains or operates a station located at a specified place.
  • E. garrisonServed chosen
    Indicates that a military unit or personnel were stationed at and performed service in a particular garrison or fortified location.
  • F. None of above.

Provenance (4 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_69d822e283fc8190a0e4c235cf880052 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb54dda1c8190bf16d17e26a2bba6 completed April 14, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde177ced48190a448cbee1f4c75bf completed May 8, 2026, 1:13 p.m.
PD Predicate disambiguation batch_69de6576f0208190aa94d995e797ac38 completed April 14, 2026, 4:04 p.m.
Created at: April 10, 2026, 1:27 a.m.