Triple
T11356195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sasin School of Management |
E268957
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
Sasin
Sasin is a leading graduate business school based in Bangkok, Thailand, known for its MBA and executive education programs.
|
E920878
|
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: Sasin | Statement: [Sasin School of Management, shortName, Sasin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sasin Context triple: [Sasin School of Management, shortName, Sasin]
-
A.
Tasiwit
Tasiwit is an alternative name for Siwi, a Berber language spoken in Egypt’s Siwa Oasis.
-
B.
Isara
Isara is the Latin name for the Isar River, a major waterway flowing through the Alps and the city of Munich in Germany.
-
C.
Nong Yai
Nong Yai is a district-level locality in Thailand known for its rural communities and agricultural landscape within Chonburi Province.
-
D.
Chaiyasongkhram
Chaiyasongkhram was a monarch who succeeded King Mangrai in ruling the Lanna Kingdom in what is now northern Thailand.
-
E.
Supachai
Supachai is a Thai economist and politician best known for serving as Director-General of the World Trade Organization and later as Secretary-General of the UN Conference on Trade and Development.
- 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: Sasin Triple: [Sasin School of Management, shortName, Sasin]
Generated description
Sasin is a leading graduate business school based in Bangkok, Thailand, known for its MBA and executive education programs.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sasin Target entity description: Sasin is a leading graduate business school based in Bangkok, Thailand, known for its MBA and executive education programs.
-
A.
Tasiwit
Tasiwit is an alternative name for Siwi, a Berber language spoken in Egypt’s Siwa Oasis.
-
B.
Isara
Isara is the Latin name for the Isar River, a major waterway flowing through the Alps and the city of Munich in Germany.
-
C.
Nong Yai
Nong Yai is a district-level locality in Thailand known for its rural communities and agricultural landscape within Chonburi Province.
-
D.
Chaiyasongkhram
Chaiyasongkhram was a monarch who succeeded King Mangrai in ruling the Lanna Kingdom in what is now northern Thailand.
-
E.
Supachai
Supachai is a Thai economist and politician best known for serving as Director-General of the World Trade Organization and later as Secretary-General of the UN Conference on Trade and Development.
- 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea419afc8190b3a93141d015ebdf |
completed | April 9, 2026, 6:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e543b3cbd88190bb479ac88f8ca710 |
completed | April 19, 2026, 9:05 p.m. |
| NEDg | Description generation | batch_69e548bb7be4819093aeeaf0c048033e |
completed | April 19, 2026, 9:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e54efda820819092d6a94fa4fd21f0 |
completed | April 19, 2026, 9:54 p.m. |
Created at: April 8, 2026, 9:33 p.m.