Triple
T13428111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sukhothai period |
E313536
|
entity |
| Predicate | notableRuler |
P22
|
FINISHED |
| Object |
Lithai
Lithai was a prominent king of the Sukhothai Kingdom in 14th-century Thailand, known for consolidating royal power and promoting Theravada Buddhism and Thai culture.
|
E1040762
|
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: Lithai | Statement: [Sukhothai period, notableRuler, Lithai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lithai Context triple: [Sukhothai period, notableRuler, Lithai]
-
A.
Thái
Thái is a Vietnamese family name commonly borne by individuals such as the military leader Hoàng Văn Thái.
-
B.
Siam
Siam is a major commercial and transportation hub in central Bangkok, known for its large shopping complexes and role as a key interchange point in the city’s transit system.
-
C.
Thailand
Thailand is a Southeast Asian nation known for its rich Buddhist culture, constitutional monarchy, and role as a regional hub for tourism and trade.
-
D.
Khatai
Khatai was the poetic pen name of Shah Ismail I, the founder of the Safavid dynasty and an influential Azerbaijani-Turkic poet.
-
E.
Sasin
Sasin is a leading graduate business school based in Bangkok, Thailand, known for its MBA and executive education programs.
- 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: Lithai Triple: [Sukhothai period, notableRuler, Lithai]
Generated description
Lithai was a prominent king of the Sukhothai Kingdom in 14th-century Thailand, known for consolidating royal power and promoting Theravada Buddhism and Thai culture.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lithai Target entity description: Lithai was a prominent king of the Sukhothai Kingdom in 14th-century Thailand, known for consolidating royal power and promoting Theravada Buddhism and Thai culture.
-
A.
Thái
Thái is a Vietnamese family name commonly borne by individuals such as the military leader Hoàng Văn Thái.
-
B.
Siam
Siam is a major commercial and transportation hub in central Bangkok, known for its large shopping complexes and role as a key interchange point in the city’s transit system.
-
C.
Thailand
Thailand is a Southeast Asian nation known for its rich Buddhist culture, constitutional monarchy, and role as a regional hub for tourism and trade.
-
D.
Khatai
Khatai was the poetic pen name of Shah Ismail I, the founder of the Safavid dynasty and an influential Azerbaijani-Turkic poet.
-
E.
Sasin
Sasin is a leading graduate business school based in Bangkok, Thailand, known for its MBA and executive education programs.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed1f9208190bf5ef5b8a7ded376 |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7398984f48190adaa1963d261d538 |
completed | May 3, 2026, 12:03 p.m. |
| NEDg | Description generation | batch_69f73b4052188190bfb583380460adab |
completed | May 3, 2026, 12:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f73c0e01288190be3e3abc73df7780 |
completed | May 3, 2026, 12:14 p.m. |
Created at: April 9, 2026, 9:40 p.m.