Triple
T1675614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sharif University of Technology |
E36224
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
SUT
SUT is the commonly used abbreviation for Sharif University of Technology, a leading science and engineering university in Iran.
|
E189594
|
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: SUT | Statement: [Sharif University of Technology, shortName, SUT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SUT Context triple: [Sharif University of Technology, shortName, SUT]
-
A.
sot
sot is the ISO 639-3 language code for Sesotho, a Southern Bantu language spoken primarily in Lesotho and South Africa.
-
B.
SACT
SACT is the Supreme Allied Commander Transformation, the NATO strategic commander responsible for leading the alliance’s military transformation and capability development.
-
C.
Tus
Tus is an ancient city in northeastern Iran, renowned as a cultural and literary center and traditionally regarded as the birthplace and home of the Persian epic poet Ferdowsi.
-
D.
Sibutu Sama
Sibutu Sama is a regional variety of the Sama–Bajaw language cluster spoken primarily on Sibutu Island in the southern Philippines.
-
E.
SU
SU was the two-letter country code used to represent the former Soviet Union in various international standards and systems.
- 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: SUT Triple: [Sharif University of Technology, shortName, SUT]
Generated description
SUT is the commonly used abbreviation for Sharif University of Technology, a leading science and engineering university in Iran.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SUT Target entity description: SUT is the commonly used abbreviation for Sharif University of Technology, a leading science and engineering university in Iran.
-
A.
sot
sot is the ISO 639-3 language code for Sesotho, a Southern Bantu language spoken primarily in Lesotho and South Africa.
-
B.
SACT
SACT is the Supreme Allied Commander Transformation, the NATO strategic commander responsible for leading the alliance’s military transformation and capability development.
-
C.
Tus
Tus is an ancient city in northeastern Iran, renowned as a cultural and literary center and traditionally regarded as the birthplace and home of the Persian epic poet Ferdowsi.
-
D.
Sibutu Sama
Sibutu Sama is a regional variety of the Sama–Bajaw language cluster spoken primarily on Sibutu Island in the southern Philippines.
-
E.
SU
SU was the two-letter country code used to represent the former Soviet Union in various international standards and systems.
- 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_69a886139ed081909af0940aa9313512 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa625cb1a08190bf7b138c5bfb90b2 |
completed | March 6, 2026, 5:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad71b5729c8190b410893d62bedb13 |
completed | March 8, 2026, 12:55 p.m. |
| NEDg | Description generation | batch_69ad728cb27c8190802b30afc5e259e2 |
completed | March 8, 2026, 12:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad72fa21208190b596bfdfc69043bd |
completed | March 8, 2026, 1 p.m. |
Created at: March 4, 2026, 7:29 p.m.