Triple
T12466784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kinta Valley |
E297943
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Gopeng
Gopeng is a historic tin-mining town in the Kinta Valley of Perak, Malaysia, known today for its nearby caves, waterfalls, and outdoor adventure tourism.
|
E1044105
|
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: Gopeng | Statement: [Kinta Valley, containsTown, Gopeng]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gopeng Context triple: [Kinta Valley, containsTown, Gopeng]
-
A.
Ipoh
Ipoh is a prominent city in northwestern Peninsular Malaysia, known for its colonial-era architecture, limestone hills and caves, and vibrant food scene.
-
B.
Kuala Kangsar
Kuala Kangsar is a historic royal town in the Malaysian state of Perak, known as the traditional seat of the Perak Sultanate.
-
C.
Kluang
Kluang is a town and district capital located in the central part of Johor, Malaysia, known for its coffee culture and surrounding agricultural areas.
-
D.
Lumut
Lumut is a coastal town in the Malaysian state of Perak, known as a gateway to Pangkor Island and as a naval and port town.
-
E.
Lumut
Lumut is a small island located within Indonesia’s Bangka Belitung Islands province, known for its coastal tropical setting.
- 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: Gopeng Triple: [Kinta Valley, containsTown, Gopeng]
Generated description
Gopeng is a historic tin-mining town in the Kinta Valley of Perak, Malaysia, known today for its nearby caves, waterfalls, and outdoor adventure tourism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gopeng Target entity description: Gopeng is a historic tin-mining town in the Kinta Valley of Perak, Malaysia, known today for its nearby caves, waterfalls, and outdoor adventure tourism.
-
A.
Ipoh
Ipoh is a prominent city in northwestern Peninsular Malaysia, known for its colonial-era architecture, limestone hills and caves, and vibrant food scene.
-
B.
Kuala Kangsar
Kuala Kangsar is a historic royal town in the Malaysian state of Perak, known as the traditional seat of the Perak Sultanate.
-
C.
Kluang
Kluang is a town and district capital located in the central part of Johor, Malaysia, known for its coffee culture and surrounding agricultural areas.
-
D.
Lumut
Lumut is a coastal town in the Malaysian state of Perak, known as a gateway to Pangkor Island and as a naval and port town.
-
E.
Lumut
Lumut is a small island located within Indonesia’s Bangka Belitung Islands province, known for its coastal tropical setting.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94db979c481908778188794b2c08e |
completed | April 10, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75464d85c8190a4c27f22cfd7dc96 |
completed | May 3, 2026, 1:57 p.m. |
| NEDg | Description generation | batch_69f75595c874819088c192f9f5d31f01 |
completed | May 3, 2026, 2:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7560bf3f88190847adca083f236fe |
completed | May 3, 2026, 2:05 p.m. |
Created at: April 8, 2026, 9:56 p.m.