Triple
T8651989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jempol District |
E205121
|
entity |
| Predicate | stateConstituency |
P19338
|
FINISHED |
| Object |
Serting
Serting is a state constituency in Malaysia that is represented in the Negeri Sembilan State Legislative Assembly.
|
E748528
|
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: Serting | Statement: [Jempol District, stateConstituency, Serting]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Serting Context triple: [Jempol District, stateConstituency, Serting]
-
A.
Segamat
Segamat is a prominent inland town and agricultural hub in the northern part of Johor, Malaysia, known for its rubber and oil palm plantations and role as a regional commercial center.
-
B.
Guting
Guting is a key Taipei Metro station in central Taipei that serves as a transfer point between multiple subway lines.
-
C.
Sorau
Sorau is a historic town in present-day Żary, western Poland, that was formerly part of Prussia and is known for its shifting political affiliations in Central European history.
-
D.
Sieda
Sieda is the surname of Abdulbaset Sieda, a Syrian-Kurdish academic and opposition political figure.
-
E.
Sennan
Sennan is a coastal city in Osaka Prefecture, Japan, known for its proximity to Kansai International Airport and its role as part of the greater Osaka metropolitan area.
- 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: Serting Triple: [Jempol District, stateConstituency, Serting]
Generated description
Serting is a state constituency in Malaysia that is represented in the Negeri Sembilan State Legislative Assembly.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Serting Target entity description: Serting is a state constituency in Malaysia that is represented in the Negeri Sembilan State Legislative Assembly.
-
A.
Segamat
Segamat is a prominent inland town and agricultural hub in the northern part of Johor, Malaysia, known for its rubber and oil palm plantations and role as a regional commercial center.
-
B.
Guting
Guting is a key Taipei Metro station in central Taipei that serves as a transfer point between multiple subway lines.
-
C.
Sorau
Sorau is a historic town in present-day Żary, western Poland, that was formerly part of Prussia and is known for its shifting political affiliations in Central European history.
-
D.
Sieda
Sieda is the surname of Abdulbaset Sieda, a Syrian-Kurdish academic and opposition political figure.
-
E.
Sennan
Sennan is a coastal city in Osaka Prefecture, Japan, known for its proximity to Kansai International Airport and its role as part of the greater Osaka metropolitan area.
- 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_69ca834e56848190abb0eeaec9dedd32 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5c2d852081908901f5d2a47035b0 |
completed | March 31, 2026, 11:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ceccd1d7f88190a5440581325eac63 |
completed | April 2, 2026, 8:08 p.m. |
| NEDg | Description generation | batch_69cece8c4bdc8190988990c675f50f86 |
completed | April 2, 2026, 8:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cecf3a0e78819082cc7c43eceae309 |
completed | April 2, 2026, 8:19 p.m. |
Created at: March 30, 2026, 6:29 p.m.