Triple

T1550053
Position Surface form Disambiguated ID Type / Status
Subject Battle off Cape Engaño E33068 entity
Predicate JapaneseWarshipSunk P821 FINISHED
Object Tama
Tama was a Japanese light cruiser of the Imperial Japanese Navy that served in World War II before being sunk during the Battle off Cape Engaño in 1944.
 E175798 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: Tama | Statement: [Battle off Cape Engaño, JapaneseWarshipSunk, Tama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tama
Context triple: [Battle off Cape Engaño, JapaneseWarshipSunk, Tama]
  • A. Tama
    Tama is a region in western Tokyo, Japan, encompassing several suburban cities and towns that serve as residential and commercial areas for the greater Tokyo metropolis.
  • B. Hama
    Hama is a major city in west-central Syria, historically known for its ancient waterwheels (norias) on the Orontes River and its role as an important agricultural and industrial center.
  • C. Tamambo
    Tamambo is an Oceanic Austronesian language spoken primarily on Malo Island in Vanuatu.
  • D. Tigak
    Tigak is an Austronesian language of the Meso-Melanesian subgroup spoken primarily in parts of Papua New Guinea.
  • E. Tuyo
    "Tuyo" is a bolero-style song by Rodrigo Amarante, best known as the haunting opening theme of the television series *Narcos*.
  • 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: Tama
Triple: [Battle off Cape Engaño, JapaneseWarshipSunk, Tama]
Generated description
Tama was a Japanese light cruiser of the Imperial Japanese Navy that served in World War II before being sunk during the Battle off Cape Engaño in 1944.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tama
Target entity description: Tama was a Japanese light cruiser of the Imperial Japanese Navy that served in World War II before being sunk during the Battle off Cape Engaño in 1944.
  • A. Tama
    Tama is a region in western Tokyo, Japan, encompassing several suburban cities and towns that serve as residential and commercial areas for the greater Tokyo metropolis.
  • B. Hama
    Hama is a major city in west-central Syria, historically known for its ancient waterwheels (norias) on the Orontes River and its role as an important agricultural and industrial center.
  • C. Tamambo
    Tamambo is an Oceanic Austronesian language spoken primarily on Malo Island in Vanuatu.
  • D. Tigak
    Tigak is an Austronesian language of the Meso-Melanesian subgroup spoken primarily in parts of Papua New Guinea.
  • E. Tuyo
    "Tuyo" is a bolero-style song by Rodrigo Amarante, best known as the haunting opening theme of the television series *Narcos*.
  • 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_69a885ee6db8819099502bc5ce8af881 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa61ddc9908190a4afca1c24400817 completed March 6, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad30a29ae88190ab1b2ca97b8ed09c completed March 8, 2026, 8:17 a.m.
NEDg Description generation batch_69ad3196e92481909bd09e6c765a9698 completed March 8, 2026, 8:21 a.m.
NED2 Entity disambiguation (via description) batch_69ad32391ed881909826a80a90f18cb4 completed March 8, 2026, 8:24 a.m.
Created at: March 4, 2026, 7:26 p.m.