Triple

T17140496
Position Surface form Disambiguated ID Type / Status
Subject USM E415947 entity
Predicate abbreviation P43 FINISHED
Object USM unclear NED1 NE FINISHED

How this triple was built (2 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: USM | Statement: [USM, abbreviation, USM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: USM
Context triple: [USM, abbreviation, USM]
  • A. USM
    USM (User-based Security Model) is the SNMPv3 security framework that provides user-level authentication, privacy (encryption), and access control for Simple Network Management Protocol communications.
  • B. USM
    USM is the stock ticker symbol for United States Cellular Corporation, a regional wireless telecommunications provider in the United States.
  • C. USM
    USM is the abbreviation for the U.S. Department of State’s Under Secretary for Management, the senior official overseeing the department’s administrative, budgetary, and logistical functions.
  • D. USM
    USM is a public higher education system in the state of Maryland that oversees multiple universities and research institutions.
  • E. USM
    USM is a public research university located in Hattiesburg, Mississippi, known for its programs in the arts, sciences, and education.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

Provenance (3 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_69d886d15af4819092f92f8a129763e6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f2d44a508190a3a149c3a64957f5 completed April 18, 2026, 9:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a014154b9848190ac01602eb01ae710 completed May 11, 2026, 2:39 a.m.
Created at: April 10, 2026, 5:36 a.m.