Triple
T13047282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isan |
E327356
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
Kalasin
Kalasin is a provincial capital city in northeastern Thailand known for its rich Isan culture and nearby dinosaur fossil sites.
|
E1018245
|
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: Kalasin | Statement: [Isan, hasMajorCity, Kalasin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kalasin Context triple: [Isan, hasMajorCity, Kalasin]
-
A.
Thakot
Thakot is a town in Pakistan’s Khyber Pakhtunkhwa province, situated along the Indus River and serving as a key junction on routes linking the northern mountainous regions with the rest of the country.
-
B.
Supayalay
Supayalay was a Burmese queen consort of the Konbaung Dynasty and one of the principal wives of the last king of Burma, Thibaw Min.
-
C.
Pak Kret
Pak Kret is a major suburban city in the Bangkok Metropolitan Region of central Thailand, known for its residential communities and proximity to the Chao Phraya River.
-
D.
Tharmada
Tharmada is a town in central Saudi Arabia where the Central Najdi dialect of Arabic is commonly spoken.
-
E.
Bang Pu
Bang Pu is a coastal area in Thailand known for its seaside scenery, pier, and large flocks of migratory seagulls that attract many visitors.
- 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: Kalasin Triple: [Isan, hasMajorCity, Kalasin]
Generated description
Kalasin is a provincial capital city in northeastern Thailand known for its rich Isan culture and nearby dinosaur fossil sites.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kalasin Target entity description: Kalasin is a provincial capital city in northeastern Thailand known for its rich Isan culture and nearby dinosaur fossil sites.
-
A.
Thakot
Thakot is a town in Pakistan’s Khyber Pakhtunkhwa province, situated along the Indus River and serving as a key junction on routes linking the northern mountainous regions with the rest of the country.
-
B.
Supayalay
Supayalay was a Burmese queen consort of the Konbaung Dynasty and one of the principal wives of the last king of Burma, Thibaw Min.
-
C.
Pak Kret
Pak Kret is a major suburban city in the Bangkok Metropolitan Region of central Thailand, known for its residential communities and proximity to the Chao Phraya River.
-
D.
Tharmada
Tharmada is a town in central Saudi Arabia where the Central Najdi dialect of Arabic is commonly spoken.
-
E.
Bang Pu
Bang Pu is a coastal area in Thailand known for its seaside scenery, pier, and large flocks of migratory seagulls that attract many visitors.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d9805125e481908ed56f708de98a9e |
completed | April 10, 2026, 10:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbd8f1308190992c0bd832e1b05e |
completed | May 3, 2026, 4:15 a.m. |
| NEDg | Description generation | batch_69f6cd98d29c8190b33cb2cc6c477b1d |
completed | May 3, 2026, 4:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6ce23ca208190960409130c4c52a9 |
completed | May 3, 2026, 4:25 a.m. |
Created at: April 9, 2026, 8:57 p.m.