Triple
T8302322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thai Wikinews |
E194376
|
entity |
| Predicate | hasSisterProject |
P14971
|
FINISHED |
| Object |
Thai Wikivoyage
Thai Wikivoyage is the Thai-language edition of Wikivoyage, a collaboratively written, free online travel guide.
|
E723761
|
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: Thai Wikivoyage | Statement: [Thai Wikinews, hasSisterProject, Thai Wikivoyage]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thai Wikivoyage Context triple: [Thai Wikinews, hasSisterProject, Thai Wikivoyage]
-
A.
THAI
THAI is the airline callsign used by Thai Airways International, the flag carrier of Thailand.
-
B.
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.
-
C.
Thai Wikinews
Thai Wikinews is the Thai-language edition of the Wikinews project, offering collaboratively written, free-content news articles for Thai-speaking readers.
-
D.
Pattaya
Pattaya is a major Thai coastal city known for its vibrant nightlife, beaches, and role as a leading international tourist resort.
-
E.
Krabi
Krabi is a coastal province in southern Thailand renowned for its dramatic limestone cliffs, clear turquoise waters, and island-hopping beaches like Railay and the Phi Phi Islands.
- 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: Thai Wikivoyage Triple: [Thai Wikinews, hasSisterProject, Thai Wikivoyage]
Generated description
Thai Wikivoyage is the Thai-language edition of Wikivoyage, a collaboratively written, free online travel guide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Thai Wikivoyage Target entity description: Thai Wikivoyage is the Thai-language edition of Wikivoyage, a collaboratively written, free online travel guide.
-
A.
THAI
THAI is the airline callsign used by Thai Airways International, the flag carrier of Thailand.
-
B.
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.
-
C.
Thai Wikinews
Thai Wikinews is the Thai-language edition of the Wikinews project, offering collaboratively written, free-content news articles for Thai-speaking readers.
-
D.
Pattaya
Pattaya is a major Thai coastal city known for its vibrant nightlife, beaches, and role as a leading international tourist resort.
-
E.
Krabi
Krabi is a coastal province in southern Thailand renowned for its dramatic limestone cliffs, clear turquoise waters, and island-hopping beaches like Railay and the Phi Phi Islands.
- 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_69ca82e613e88190bf8139669bbd0d53 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7e8a45348190a7895b33abcb64c9 |
completed | March 31, 2026, 7:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd68c2a14c81908388ecdd22315390 |
completed | April 1, 2026, 6:49 p.m. |
| NEDg | Description generation | batch_69cd6d58032c8190ba99f78670924ae5 |
completed | April 1, 2026, 7:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cd7e5be1108190afbc65b69a7700f2 |
completed | April 1, 2026, 8:21 p.m. |
Created at: March 30, 2026, 5:53 p.m.