Triple
T10038422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Musikhochschule Lübeck |
E205231
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
MHL
MHL is the abbreviation for Musikhochschule Lübeck, a renowned German university-level institution specializing in music education and performance.
|
E837391
|
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: MHL | Statement: [Musikhochschule Lübeck, shortName, MHL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MHL Context triple: [Musikhochschule Lübeck, shortName, MHL]
-
A.
MHL
MHL is the three-letter ISO 3166-1 alpha-3 country code representing the Republic of the Marshall Islands.
-
B.
MHL
MHL is the commonly used abbreviation for the International Hockey League, a professional ice hockey organization.
-
C.
MHL
The MHL is Russia’s top junior ice hockey league, serving as a key development system for young players aiming to reach professional levels such as the KHL.
-
D.
MHL
MHL is an abbreviation that can refer to various entities, most commonly the Mobile High-Definition Link technology standard for transmitting audio and video from mobile devices to displays.
-
E.
MHL-B
MHL-B is a Russian junior ice hockey league that serves as the second-tier developmental competition beneath the main Junior Hockey League (MHL).
- 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: MHL Triple: [Musikhochschule Lübeck, shortName, MHL]
Generated description
MHL is the abbreviation for Musikhochschule Lübeck, a renowned German university-level institution specializing in music education and performance.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MHL Target entity description: MHL is the abbreviation for Musikhochschule Lübeck, a renowned German university-level institution specializing in music education and performance.
-
A.
MHL
MHL is the three-letter ISO 3166-1 alpha-3 country code representing the Republic of the Marshall Islands.
-
B.
MHL
MHL is the commonly used abbreviation for the International Hockey League, a professional ice hockey organization.
-
C.
MHL
The MHL is Russia’s top junior ice hockey league, serving as a key development system for young players aiming to reach professional levels such as the KHL.
-
D.
MHL
MHL is an abbreviation that can refer to various entities, most commonly the Mobile High-Definition Link technology standard for transmitting audio and video from mobile devices to displays.
-
E.
MHL-B
MHL-B is a Russian junior ice hockey league that serves as the second-tier developmental competition beneath the main Junior Hockey League (MHL).
- 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_69ca834f70e88190b2d74828b7767ec1 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcee04afc8190904704d66e23a432 |
completed | April 2, 2026, 2:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d282608d688190832c37442f53099a |
completed | April 5, 2026, 3:40 p.m. |
| NEDg | Description generation | batch_69d2840bb2e881908a7e7a40229769e0 |
completed | April 5, 2026, 3:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d2847c9bb881908a6330dfe2c2c1a4 |
completed | April 5, 2026, 3:49 p.m. |
Created at: March 30, 2026, 8:55 p.m.