Triple

T12506550
Position Surface form Disambiguated ID Type / Status
Subject Mureș County E298961 entity
Predicate ISO3166-2Code P208 FINISHED
Object RO-MS
RO-MS is the ISO 3166-2 subdivision code assigned to Mureș County in Romania.
 E986768 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: RO-MS | Statement: [Mureș County, ISO3166-2Code, RO-MS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RO-MS
Context triple: [Mureș County, ISO3166-2Code, RO-MS]
  • A. BR-MS
    BR-MS is the ISO 3166-2 subdivision code that uniquely identifies the Brazilian state of Mato Grosso do Sul.
  • B. MSR
    MSR is the ICAO airline designator used to identify EgyptAir in international aviation operations.
  • C. MS-2
    MS-2 is the abbreviated designation for Mississippi's 2nd congressional district, a U.S. House of Representatives district encompassing much of the Mississippi Delta and parts of Jackson.
  • D. MRM
    MRM is a UN-established system that systematically documents, verifies, and reports grave violations committed against children in armed conflict to support accountability and protection efforts.
  • E. MSA
    MSA is a common abbreviation for a metropolitan statistical area, a region defined by the U.S. Office of Management and Budget for statistical and demographic analysis.
  • 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: RO-MS
Triple: [Mureș County, ISO3166-2Code, RO-MS]
Generated description
RO-MS is the ISO 3166-2 subdivision code assigned to Mureș County in Romania.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: RO-MS
Target entity description: RO-MS is the ISO 3166-2 subdivision code assigned to Mureș County in Romania.
  • A. BR-MS
    BR-MS is the ISO 3166-2 subdivision code that uniquely identifies the Brazilian state of Mato Grosso do Sul.
  • B. MSR
    MSR is the ICAO airline designator used to identify EgyptAir in international aviation operations.
  • C. MS-2
    MS-2 is the abbreviated designation for Mississippi's 2nd congressional district, a U.S. House of Representatives district encompassing much of the Mississippi Delta and parts of Jackson.
  • D. MRM
    MRM is a UN-established system that systematically documents, verifies, and reports grave violations committed against children in armed conflict to support accountability and protection efforts.
  • E. MSA
    MSA is a common abbreviation for a metropolitan statistical area, a region defined by the U.S. Office of Management and Budget for statistical and demographic analysis.
  • 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_69d6ada4cd388190ae3bbf83ff87057a completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94dfddf38819099263b8b1e804736 completed April 10, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64bb778e081909bab2ef87226c6a0 completed May 2, 2026, 7:08 p.m.
NEDg Description generation batch_69f64ce1b0ec8190bcbd245255e548b5 completed May 2, 2026, 7:13 p.m.
NED2 Entity disambiguation (via description) batch_69f64da735f48190b051ce173c13e5b2 completed May 2, 2026, 7:16 p.m.
Created at: April 8, 2026, 9:57 p.m.