Triple
T1880108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Selangor |
E39832
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Klang |
E210327
|
NE FINISHED |
How this triple was built (2 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: Klang | Statement: [Selangor, contains, Klang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Klang Context triple: [Selangor, contains, Klang]
-
A.
Klang
chosen
Klang is a historic town and major urban center in the state of Selangor, Malaysia, known for its royal heritage and proximity to the Port Klang industrial hub.
-
B.
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.
-
C.
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.
-
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.
Kertajaya
Kertajaya was a 13th-century king of the Kediri Kingdom in Java, remembered for his conflict with the emerging Singhasari kingdom and his role in the region’s political transition.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a88633e4fc8190b7eb40463e048ec5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0fa3d388190993073ffb0f60a84 |
completed | March 7, 2026, 5 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeae44f6c8190a5924609863030a4 |
completed | March 8, 2026, 9:32 p.m. |
Created at: March 4, 2026, 7:34 p.m.