Triple

T2937212
Position Surface form Disambiguated ID Type / Status
Subject M48 Patton tank E79295 entity
Predicate variant P4680 FINISHED
Object Magach 3
Magach 3 is an Israeli upgraded version of the American M48 Patton tank, featuring improved armor, firepower, and mobility tailored to Israel Defense Forces requirements.
 E312067 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: Magach 3 | Statement: [M48 Patton tank, variant, Magach 3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Magach 3
Context triple: [M48 Patton tank, variant, Magach 3]
  • A. MAG
    MAG is a major British airport operator that owns and manages several UK airports, including Manchester Airport.
  • B. Magazia
    Magazia is a small village on the Greek island of Paxos, known for its traditional character and tranquil, rural setting.
  • C. MagE
    MagE is a medium-resolution optical echellette spectrograph used on the Magellan telescopes for detailed spectroscopic studies of astronomical objects.
  • D. MGA
    MGA is a public university in Georgia, United States, offering a range of undergraduate and graduate programs across multiple campuses.
  • E. MGA
    MGA is the commonly used abbreviation for the Maryland General Assembly, the state’s bicameral legislative body.
  • 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: Magach 3
Triple: [M48 Patton tank, variant, Magach 3]
Generated description
Magach 3 is an Israeli upgraded version of the American M48 Patton tank, featuring improved armor, firepower, and mobility tailored to Israel Defense Forces requirements.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Magach 3
Target entity description: Magach 3 is an Israeli upgraded version of the American M48 Patton tank, featuring improved armor, firepower, and mobility tailored to Israel Defense Forces requirements.
  • A. MAG
    MAG is a major British airport operator that owns and manages several UK airports, including Manchester Airport.
  • B. Magazia
    Magazia is a small village on the Greek island of Paxos, known for its traditional character and tranquil, rural setting.
  • C. MagE
    MagE is a medium-resolution optical echellette spectrograph used on the Magellan telescopes for detailed spectroscopic studies of astronomical objects.
  • D. MGA
    MGA is the commonly used abbreviation for the Maryland General Assembly, the state’s bicameral legislative body.
  • E. MGA
    MGA is a public university in Georgia, United States, offering a range of undergraduate and graduate programs across multiple campuses.
  • 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_69ad8b0fbab081908f6a61567c045d8d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad983f91c48190b409d8f522cab08b completed March 8, 2026, 3:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b086837ddc8190af27c7facd629691 completed March 10, 2026, 9 p.m.
NEDg Description generation batch_69b0d15ec81c81909c22e265dd0263df completed March 11, 2026, 2:20 a.m.
NED2 Entity disambiguation (via description) batch_69b0d524994c8190b8b6ff05eee8696a completed March 11, 2026, 2:36 a.m.
Created at: March 8, 2026, 2:56 p.m.