Triple
T1853047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kelantan |
E41638
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Pasir Mas
Pasir Mas is a town in the Malaysian state of Kelantan, known as a local commercial and transport hub near the border with Thailand.
|
E207470
|
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: Pasir Mas | Statement: [Kelantan, hasTown, Pasir Mas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pasir Mas Context triple: [Kelantan, hasTown, Pasir Mas]
-
A.
Pelabuhan Ratu
Pelabuhan Ratu is a coastal town and bay in West Java, Indonesia, known for its scenic beaches, strong surf, and local fishing culture.
-
B.
Labuan
Labuan is a federal territory of Malaysia comprising a main island and several smaller ones, known as an offshore financial center and duty-free port off the coast of Borneo.
-
C.
Labuan
Labuan is a coastal town in Banten, western Java, Indonesia, known as a gateway to nearby natural attractions and marine tourism areas.
-
D.
Batam
Batam is a major Indonesian industrial and transport hub located near Singapore, known for its free-trade zone status and rapidly growing economy.
-
E.
Johor Lama
Johor Lama was a historic fortified riverine settlement that served as an important political and trading center of the Johor Sultanate in the Malay Peninsula.
- 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: Pasir Mas Triple: [Kelantan, hasTown, Pasir Mas]
Generated description
Pasir Mas is a town in the Malaysian state of Kelantan, known as a local commercial and transport hub near the border with Thailand.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pasir Mas Target entity description: Pasir Mas is a town in the Malaysian state of Kelantan, known as a local commercial and transport hub near the border with Thailand.
-
A.
Pelabuhan Ratu
Pelabuhan Ratu is a coastal town and bay in West Java, Indonesia, known for its scenic beaches, strong surf, and local fishing culture.
-
B.
Labuan
Labuan is a federal territory of Malaysia comprising a main island and several smaller ones, known as an offshore financial center and duty-free port off the coast of Borneo.
-
C.
Labuan
Labuan is a coastal town in Banten, western Java, Indonesia, known as a gateway to nearby natural attractions and marine tourism areas.
-
D.
Batam
Batam is a major Indonesian industrial and transport hub located near Singapore, known for its free-trade zone status and rapidly growing economy.
-
E.
Johor Lama
Johor Lama was a historic fortified riverine settlement that served as an important political and trading center of the Johor Sultanate in the Malay Peninsula.
- 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_69a8864a83848190a4ec02721306c511 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb06999f4819086386aafb789a368 |
completed | March 7, 2026, 4:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69add1c89bdc8190acf517a7731fa5c7 |
completed | March 8, 2026, 7:45 p.m. |
| NEDg | Description generation | batch_69add25c9c208190a576cf1123c0a2e6 |
completed | March 8, 2026, 7:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69add32803a48190b8ff08c605790f22 |
completed | March 8, 2026, 7:51 p.m. |
Created at: March 4, 2026, 7:33 p.m.