Triple
T6411723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province Wellesley |
E127721
|
entity |
| Predicate | currentLocation |
P40
|
FINISHED |
| Object | Penang state |
E55976
|
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: Penang state | Statement: [Province Wellesley, currentLocation, Penang state]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Penang state Context triple: [Province Wellesley, currentLocation, Penang state]
-
A.
Kuala Perlis
Kuala Perlis is a small coastal town in Malaysia known as a key ferry gateway to the resort island of Langkawi.
-
B.
Kedah
Kedah is a state in northwestern Peninsular Malaysia, historically significant as one of the oldest Malay kingdoms and once part of British Malaya.
-
C.
Johor
Johor is a state in southern Peninsular Malaysia known for its strategic location bordering Singapore, diverse economy, and rich Malay cultural heritage.
-
D.
Selangor
Selangor is a highly developed and populous state on the west coast of Peninsular Malaysia that surrounds the federal territories of Kuala Lumpur and Putrajaya.
-
E.
Penang
chosen
Penang is a Malaysian state and island renowned for its multicultural heritage, historic George Town, and vibrant street food scene.
- 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_69c0083723d88190b1e37b19df162c08 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c068d0f2b88190af06c208d8c01d07 |
completed | March 22, 2026, 10:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c640c48e688190981a19ce5eb2af44 |
completed | March 27, 2026, 8:33 a.m. |
Created at: March 22, 2026, 4:41 p.m.