Triple

T1272380
Position Surface form Disambiguated ID Type / Status
Subject USS Pampanito E15737 entity
Predicate hullNumber P3152 FINISHED
Object SS-383
SS-383 is the hull number of USS Pampanito, a World War II-era Balao-class submarine now preserved as a museum ship in San Francisco.
 E144683 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: SS-383 | Statement: [USS Pampanito, hullNumber, SS-383]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SS-383
Context triple: [USS Pampanito, hullNumber, SS-383]
  • A. BB-38
    BB-38 is the hull number of USS Pennsylvania, a Pennsylvania-class battleship of the United States Navy that served prominently during both World Wars.
  • B. S-23
    S-23 is an International Hydrographic Organization publication that standardizes the naming and limits of the world’s oceans and seas.
  • C. S-44
    S-44 is an International Hydrographic Organization standard that defines the accuracy and quality requirements for hydrographic surveys used in nautical charting and marine navigation.
  • D. BB-37
    BB-37 is the hull number of USS Oklahoma, a Nevada-class battleship of the United States Navy that was sunk during the attack on Pearl Harbor in 1941.
  • E. SAS-3
    SAS-3 is the third-generation Serial Attached SCSI (SAS) interface standard that significantly increases data transfer rates and performance for enterprise storage systems.
  • 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: SS-383
Triple: [USS Pampanito, hullNumber, SS-383]
Generated description
SS-383 is the hull number of USS Pampanito, a World War II-era Balao-class submarine now preserved as a museum ship in San Francisco.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SS-383
Target entity description: SS-383 is the hull number of USS Pampanito, a World War II-era Balao-class submarine now preserved as a museum ship in San Francisco.
  • A. BB-38
    BB-38 is the hull number of USS Pennsylvania, a Pennsylvania-class battleship of the United States Navy that served prominently during both World Wars.
  • B. S-23
    S-23 is an International Hydrographic Organization publication that standardizes the naming and limits of the world’s oceans and seas.
  • C. S-44
    S-44 is an International Hydrographic Organization standard that defines the accuracy and quality requirements for hydrographic surveys used in nautical charting and marine navigation.
  • D. BB-37
    BB-37 is the hull number of USS Oklahoma, a Nevada-class battleship of the United States Navy that was sunk during the attack on Pearl Harbor in 1941.
  • E. SAS-3
    SAS-3 is the third-generation Serial Attached SCSI (SAS) interface standard that significantly increases data transfer rates and performance for enterprise storage systems.
  • 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_69a4935a94308190bb92555b79032824 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4c06c033081909bc594157abaf5bb completed March 1, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac998e56488190ac3cf51563335e30 completed March 7, 2026, 9:33 p.m.
NEDg Description generation batch_69ac9a13e9548190ae1fbfeba3326cd5 completed March 7, 2026, 9:35 p.m.
NED2 Entity disambiguation (via description) batch_69ac9a96d4f081908e608a3f247bbfb2 completed March 7, 2026, 9:37 p.m.
Created at: March 1, 2026, 7:50 p.m.