Triple
T8866661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pahang River |
E211034
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object |
Jerantut
Jerantut is a town and district in central Pahang, Malaysia, known as a gateway to Taman Negara National Park.
|
E763261
|
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: Jerantut | Statement: [Pahang River, passesThrough, Jerantut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jerantut Context triple: [Pahang River, passesThrough, Jerantut]
-
A.
Lumban
Lumban is a municipality in the Philippine province of Laguna known for its traditional hand-embroidered textiles and scenic lakeside setting along Laguna de Bay.
-
B.
Kampar
Kampar is a town and district in Perak, Malaysia, historically notable as the site of a major World War II battle between British Commonwealth and Japanese forces.
-
C.
Kuala Krai
Kuala Krai is a town and district capital in the interior of Kelantan, Malaysia, known as a regional administrative and commercial center along the Kelantan River.
-
D.
Keningau
Keningau is a major inland town and administrative district in the interior region of the Malaysian state of Sabah.
-
E.
Bantia
Bantia was an ancient Oscan-speaking city in southern Italy, notable for yielding important inscriptions that illuminate the Oscan language and Italic legal traditions.
- 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: Jerantut Triple: [Pahang River, passesThrough, Jerantut]
Generated description
Jerantut is a town and district in central Pahang, Malaysia, known as a gateway to Taman Negara National Park.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jerantut Target entity description: Jerantut is a town and district in central Pahang, Malaysia, known as a gateway to Taman Negara National Park.
-
A.
Lumban
Lumban is a municipality in the Philippine province of Laguna known for its traditional hand-embroidered textiles and scenic lakeside setting along Laguna de Bay.
-
B.
Kampar
Kampar is a town and district in Perak, Malaysia, historically notable as the site of a major World War II battle between British Commonwealth and Japanese forces.
-
C.
Kuala Krai
Kuala Krai is a town and district capital in the interior of Kelantan, Malaysia, known as a regional administrative and commercial center along the Kelantan River.
-
D.
Keningau
Keningau is a major inland town and administrative district in the interior region of the Malaysian state of Sabah.
-
E.
Bantia
Bantia was an ancient Oscan-speaking city in southern Italy, notable for yielding important inscriptions that illuminate the Oscan language and Italic legal traditions.
- 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_69ca838d3c7c8190a849566d5afd2b11 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6108530c819084559f4de669ce20 |
completed | April 1, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfa0dafdf48190abc1fe1a8397e339 |
completed | April 3, 2026, 11:13 a.m. |
| NEDg | Description generation | batch_69cfa191d7d0819085a6b9bf7fa56067 |
completed | April 3, 2026, 11:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfa28b1d1c8190ab4a10ba8fa7259d |
completed | April 3, 2026, 11:20 a.m. |
Created at: March 30, 2026, 6:51 p.m.