Triple

T3733979
Position Surface form Disambiguated ID Type / Status
Subject MS in Management Studies E79134 entity
Predicate hasAbbreviation P43 FINISHED
Object MSMS
MSMS is a graduate-level degree program focused on advanced studies in management, business strategy, and organizational leadership.
 E383266 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: MSMS | Statement: [MS in Management Studies, hasAbbreviation, MSMS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MSMS
Context triple: [MS in Management Studies, hasAbbreviation, MSMS]
  • A. MAS
    MAS is the ICAO airline designator used to identify Malaysia Airlines in international aviation operations.
  • B. MAS
    MAS (Monetary Authority of Singapore) is Singapore’s central bank and integrated financial regulator, responsible for monetary policy, financial supervision, and the stability of the country’s financial system.
  • C. MAS
    MAS is the official Indian Railways station code for Chennai Central, one of the busiest and most important railway terminals in South India.
  • D. MS
    MS is the two-letter ISO 3166 country code assigned to the British Overseas Territory of Montserrat in the Caribbean.
  • E. MS
    MS is the station code for Chennai Egmore, one of the major railway terminals in Chennai, India.
  • 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: MSMS
Triple: [MS in Management Studies, hasAbbreviation, MSMS]
Generated description
MSMS is a graduate-level degree program focused on advanced studies in management, business strategy, and organizational leadership.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MSMS
Target entity description: MSMS is a graduate-level degree program focused on advanced studies in management, business strategy, and organizational leadership.
  • A. MAS
    MAS is the ICAO airline designator used to identify Malaysia Airlines in international aviation operations.
  • B. MAS
    MAS (Monetary Authority of Singapore) is Singapore’s central bank and integrated financial regulator, responsible for monetary policy, financial supervision, and the stability of the country’s financial system.
  • C. MAS
    MAS is the official Indian Railways station code for Chennai Central, one of the busiest and most important railway terminals in South India.
  • D. MS
    MS is the two-letter ISO 3166 country code assigned to the British Overseas Territory of Montserrat in the Caribbean.
  • E. MS
    MS is the station code for Chennai Egmore, one of the major railway terminals in Chennai, India.
  • 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_69ad8b0e4650819090ad7cef094285e8 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb2457f08190a6b94e9895fced2c completed March 8, 2026, 7:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4db1be1388190a887d9eca0f4f9b3 completed March 14, 2026, 3:50 a.m.
NEDg Description generation batch_69b4db81fd648190a9dd6f0ade21f14d completed March 14, 2026, 3:52 a.m.
NED2 Entity disambiguation (via description) batch_69b4dc1f3cc48190b1b53bc88a0c3577 completed March 14, 2026, 3:55 a.m.
Created at: March 8, 2026, 3:34 p.m.