Triple
T8130454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 陳平 |
E189839
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Sitiawan, Perak
Sitiawan, Perak is a coastal town in the Manjung District of Perak, Malaysia, known historically for its Chinese settler communities and as a gateway to the nearby Pangkor Island.
|
E713918
|
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: Sitiawan, Perak | Statement: [陳平, placeOfBirth, Sitiawan, Perak]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sitiawan, Perak Context triple: [陳平, placeOfBirth, Sitiawan, Perak]
-
A.
Kuala Kangsar
Kuala Kangsar is a historic royal town in the Malaysian state of Perak, known as the traditional seat of the Perak Sultanate.
-
B.
Kuala Perlis
Kuala Perlis is a small coastal town in Malaysia known as a key ferry gateway to the resort island of Langkawi.
-
C.
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.
-
D.
Lumut
Lumut is a small island located within Indonesia’s Bangka Belitung Islands province, known for its coastal tropical setting.
-
E.
Sungai Petani
Sungai Petani is a major commercial and residential town in the Malaysian state of Kedah, known as one of its largest and most rapidly developing urban centers.
- 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: Sitiawan, Perak Triple: [陳平, placeOfBirth, Sitiawan, Perak]
Generated description
Sitiawan, Perak is a coastal town in the Manjung District of Perak, Malaysia, known historically for its Chinese settler communities and as a gateway to the nearby Pangkor Island.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sitiawan, Perak Target entity description: Sitiawan, Perak is a coastal town in the Manjung District of Perak, Malaysia, known historically for its Chinese settler communities and as a gateway to the nearby Pangkor Island.
-
A.
Kuala Kangsar
Kuala Kangsar is a historic royal town in the Malaysian state of Perak, known as the traditional seat of the Perak Sultanate.
-
B.
Kuala Perlis
Kuala Perlis is a small coastal town in Malaysia known as a key ferry gateway to the resort island of Langkawi.
-
C.
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.
-
D.
Lumut
Lumut is a small island located within Indonesia’s Bangka Belitung Islands province, known for its coastal tropical setting.
-
E.
Sungai Petani
Sungai Petani is a major commercial and residential town in the Malaysian state of Kedah, known as one of its largest and most rapidly developing urban centers.
- 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_69ca82bcb4848190a9a9d036ad768642 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb43b7dbd881908a80f23090596eae |
completed | March 31, 2026, 3:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc947a7354819088c6f3cc6ab677cf |
completed | April 1, 2026, 3:43 a.m. |
| NEDg | Description generation | batch_69cc95c0b19881908521cce5ac0fe197 |
completed | April 1, 2026, 3:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc970698f88190a0869515904e50e3 |
completed | April 1, 2026, 3:54 a.m. |
Created at: March 30, 2026, 5:34 p.m.