Triple

T2497321
Position Surface form Disambiguated ID Type / Status
Subject Panther tank E52181 entity
Predicate manufacturer P490 FINISHED
Object MNH
MNH was a German company that played a key role in producing Panther tanks for the Wehrmacht during World War II.
 E271689 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: MNH | Statement: [Panther tank, manufacturer, MNH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MNH
Context triple: [Panther tank, manufacturer, MNH]
  • A. MH
    MH is the two-letter ISO 3166-1 alpha-2 country code representing the Republic of the Marshall Islands.
  • B. MH
    MH is the two-letter IATA airline designator used to identify Malaysia Airlines on tickets, timetables, and flight numbers.
  • C. MH
    MH is the official vehicle registration code assigned to the Indian state of Maharashtra.
  • D. MUHA
    MUHA is the ICAO airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
  • E. Muh-he-con-neok
    Muh-he-con-neok is an alternative historical name for the Mahican, a Native American people originally from the Hudson River Valley region.
  • 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: MNH
Triple: [Panther tank, manufacturer, MNH]
Generated description
MNH was a German company that played a key role in producing Panther tanks for the Wehrmacht during World War II.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MNH
Target entity description: MNH was a German company that played a key role in producing Panther tanks for the Wehrmacht during World War II.
  • A. MH
    MH is the two-letter ISO 3166-1 alpha-2 country code representing the Republic of the Marshall Islands.
  • B. MH
    MH is the two-letter IATA airline designator used to identify Malaysia Airlines on tickets, timetables, and flight numbers.
  • C. MH
    MH is the official vehicle registration code assigned to the Indian state of Maharashtra.
  • D. MUHA
    MUHA is the ICAO airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
  • E. Muh-he-con-neok
    Muh-he-con-neok is an alternative historical name for the Mahican, a Native American people originally from the Hudson River Valley region.
  • 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_69ab4955111c8190835bf619adec21ff completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd1ad2f8c81908853e97d75081e84 completed March 7, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1f9be594819099a03a2784691124 completed March 9, 2026, 7:29 p.m.
NEDg Description generation batch_69af200e2db4819085851a45213edc89 completed March 9, 2026, 7:31 p.m.
NED2 Entity disambiguation (via description) batch_69af208dfab081909d706aad8ff5f615 completed March 9, 2026, 7:33 p.m.
Created at: March 6, 2026, 9:46 p.m.