Triple

T8118086
Position Surface form Disambiguated ID Type / Status
Subject Gary Kildall E189530 entity
Predicate notableWork P4 FINISHED
Object MP/M
MP/M is a multi-user, multitasking operating system developed by Gary Kildall as an advanced, multi-terminal extension of CP/M for microcomputers.
 E713571 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: MP/M | Statement: [Gary Kildall, notableWork, MP/M]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MP/M
Context triple: [Gary Kildall, notableWork, MP/M]
  • A. MP
    MP is the reporting mark for the Missouri Pacific Railroad, a major former U.S. Class I railroad that operated across the Midwest and Southwest.
  • B. MP
    MP is the two-letter ISO 3166-1 alpha-2 country code assigned to the Northern Mariana Islands.
  • C. MP
    MP is the IATA airline designator assigned to Martinair, a Dutch cargo and former passenger airline based in the Netherlands.
  • D. MP
    MP is the vehicle registration code for the Indian state of Madhya Pradesh.
  • E. MMP
    MMP is a hybrid electoral system that combines single-member district representation with proportional party lists to align a legislature’s overall seat distribution with parties’ share of the vote.
  • 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: MP/M
Triple: [Gary Kildall, notableWork, MP/M]
Generated description
MP/M is a multi-user, multitasking operating system developed by Gary Kildall as an advanced, multi-terminal extension of CP/M for microcomputers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MP/M
Target entity description: MP/M is a multi-user, multitasking operating system developed by Gary Kildall as an advanced, multi-terminal extension of CP/M for microcomputers.
  • A. MP
    MP is the reporting mark for the Missouri Pacific Railroad, a major former U.S. Class I railroad that operated across the Midwest and Southwest.
  • B. MP
    MP is the two-letter ISO 3166-1 alpha-2 country code assigned to the Northern Mariana Islands.
  • C. MP
    MP is the vehicle registration code for the Indian state of Madhya Pradesh.
  • D. MP
    MP is the IATA airline designator assigned to Martinair, a Dutch cargo and former passenger airline based in the Netherlands.
  • E. MMP
    MMP is a hybrid electoral system that combines single-member district representation with proportional party lists to align a legislature’s overall seat distribution with parties’ share of the vote.
  • 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_69ca82baad008190ab2859712b9b1607 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb435737c08190a4e311d4d990b4ef completed March 31, 2026, 3:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc944439488190b95788e3a77ee732 completed April 1, 2026, 3:43 a.m.
NEDg Description generation batch_69cc95c0b19881908521cce5ac0fe197 completed April 1, 2026, 3:49 a.m.
NED2 Entity disambiguation (via description) batch_69cc96fa03d881909a1eeed6af9a3149 completed April 1, 2026, 3:54 a.m.
Created at: March 30, 2026, 5:33 p.m.