Triple
T5602218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manipal Institute of Technology |
E147145
|
entity |
| Predicate | offersDegree |
P49
|
FINISHED |
| Object |
MCA
MCA is a postgraduate professional degree in computer applications that focuses on advanced software development, programming, and IT skills.
|
E533758
|
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: MCA | Statement: [Manipal Institute of Technology, offersDegree, MCA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MCA Context triple: [Manipal Institute of Technology, offersDegree, MCA]
-
A.
MCA
MCA was a major American record label and entertainment company known for signing prominent artists and producing a wide range of popular music releases.
-
B.
MCA
MCA is the UK government executive agency responsible for maritime safety, search and rescue coordination, and preventing pollution from ships in UK waters.
-
C.
MCA
MCA is a prominent Algerian football club based in Algiers, officially known as Mouloudia Club d'Alger.
-
D.
MCC
MCC is the abbreviated name of Belgium’s naval branch within the Belgian Armed Forces.
-
E.
MCC
MCC is one of the shorter companion races of the Ultra-Trail du Mont-Blanc trail-running event, typically designed for newer trail runners and local participants.
- 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: MCA Triple: [Manipal Institute of Technology, offersDegree, MCA]
Generated description
MCA is a postgraduate professional degree in computer applications that focuses on advanced software development, programming, and IT skills.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MCA Target entity description: MCA is a postgraduate professional degree in computer applications that focuses on advanced software development, programming, and IT skills.
-
A.
MCA
MCA was a major American record label and entertainment company known for signing prominent artists and producing a wide range of popular music releases.
-
B.
MCA
MCA is the UK government executive agency responsible for maritime safety, search and rescue coordination, and preventing pollution from ships in UK waters.
-
C.
MCA
MCA is a prominent Algerian football club based in Algiers, officially known as Mouloudia Club d'Alger.
-
D.
MCC
MCC is the abbreviated name of Belgium’s naval branch within the Belgian Armed Forces.
-
E.
MCC
MCC is one of the shorter companion races of the Ultra-Trail du Mont-Blanc trail-running event, typically designed for newer trail runners and local participants.
- 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_69c009043d648190a7af89698ccf1e3e |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020dbd6dc8190ba011876c205754e |
completed | March 22, 2026, 5:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c02873b1dc8190b11a6c069f3e4f7e |
completed | March 22, 2026, 5:35 p.m. |
| NEDg | Description generation | batch_69c035f54f6c8190badbfd800012c399 |
completed | March 22, 2026, 6:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c036f0edb48190bfa74f7f2c9d9ab1 |
completed | March 22, 2026, 6:37 p.m. |
Created at: March 22, 2026, 3:39 p.m.