Triple
T13377882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taiyuan University of Technology |
E319236
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
TYUT
TYUT is the commonly used abbreviation for Taiyuan University of Technology, a major public engineering-focused university in Taiyuan, Shanxi, China.
|
E1036265
|
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: TYUT | Statement: [Taiyuan University of Technology, shortName, TYUT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TYUT Context triple: [Taiyuan University of Technology, shortName, TYUT]
-
A.
UTU
UTU is the commonly used abbreviation for the University of Turku, a major multidisciplinary university in Turku, Finland.
-
B.
TUDN
TUDN is a Spanish-language sports television network and media brand focused on soccer and other sports, primarily serving audiences in the United States and Mexico.
-
C.
Tongmyong University
Tongmyong University is a higher education institution located in Busan, South Korea, offering a range of undergraduate and graduate programs.
-
D.
KNTU
KNTU is the ICAO airport code for Naval Air Station Oceana, a major United States Navy jet base located in Virginia Beach, Virginia.
-
E.
ZTU
ZTU is the IATA station code assigned to a specific passenger rail station in Miami, Florida, used for ticketing and travel logistics.
- 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: TYUT Triple: [Taiyuan University of Technology, shortName, TYUT]
Generated description
TYUT is the commonly used abbreviation for Taiyuan University of Technology, a major public engineering-focused university in Taiyuan, Shanxi, China.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TYUT Target entity description: TYUT is the commonly used abbreviation for Taiyuan University of Technology, a major public engineering-focused university in Taiyuan, Shanxi, China.
-
A.
UTU
UTU is the commonly used abbreviation for the University of Turku, a major multidisciplinary university in Turku, Finland.
-
B.
TUDN
TUDN is a Spanish-language sports television network and media brand focused on soccer and other sports, primarily serving audiences in the United States and Mexico.
-
C.
Tongmyong University
Tongmyong University is a higher education institution located in Busan, South Korea, offering a range of undergraduate and graduate programs.
-
D.
KNTU
KNTU is the ICAO airport code for Naval Air Station Oceana, a major United States Navy jet base located in Virginia Beach, Virginia.
-
E.
ZTU
ZTU is the IATA station code assigned to a specific passenger rail station in Miami, Florida, used for ticketing and travel logistics.
- 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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadce56c6c8190adf4e19f6d1bc233 |
completed | April 11, 2026, 11:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f726893a8c8190b26b5f7c7fb96f1f |
completed | May 3, 2026, 10:42 a.m. |
| NEDg | Description generation | batch_69f7276776ec81908769cd9f1cc4707e |
completed | May 3, 2026, 10:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7280cbb6c819090bee7862e00b900 |
completed | May 3, 2026, 10:48 a.m. |
Created at: April 9, 2026, 9:33 p.m.