Triple

T1584065
Position Surface form Disambiguated ID Type / Status
Subject Mobile, Alabama E34031 entity
Predicate hasPort P35 FINISHED
Object Port of Mobile E76144 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: Port of Mobile | Statement: [Mobile, Alabama, hasPort, Port of Mobile]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Port of Mobile
Context triple: [Mobile, Alabama, hasPort, Port of Mobile]
  • A. Port of Mobile chosen
    The Port of Mobile is a major deep-water seaport in Alabama that serves as a key hub for international trade, shipping, and transportation infrastructure in the southeastern United States.
  • B. Biloxi
    Biloxi is a coastal Mississippi city known for its beaches, casinos, and seafood industry along the Gulf of Mexico.
  • C. Port of Savannah
    The Port of Savannah is one of the busiest and fastest-growing container seaports in the United States, serving as a major logistics and trade hub on the U.S. East Coast.
  • D. Port of Corpus Christi
    The Port of Corpus Christi is one of the largest and busiest U.S. seaports, serving as a major hub for energy exports and industrial shipping on the Texas coast.
  • E. Port of Tampa
    The Port of Tampa is a major deep-water seaport in Florida that serves as a key hub for cargo shipping, petroleum imports, and cruise operations in the southeastern United States.
  • 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_69a885fceb2c8190b47e0f7c0aefbff0 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a908f0e72c8190bb7a2a0c77379060 completed March 5, 2026, 4:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad4035dd7c8190817301c0a2b0b938 completed March 8, 2026, 9:24 a.m.
Created at: March 4, 2026, 7:27 p.m.