Triple
T7503387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dinding Islands |
E177324
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Lumut |
E206262
|
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: Lumut | Statement: [Dinding Islands, locatedNear, Lumut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lumut Context triple: [Dinding Islands, locatedNear, Lumut]
-
A.
Lumut
chosen
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.
-
B.
Lumut
Lumut is a small island located within Indonesia’s Bangka Belitung Islands province, known for its coastal tropical setting.
-
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.
Teluk Intan
Teluk Intan is a historic riverside town in the Malaysian state of Perak, known for its iconic leaning clock tower and colonial-era architecture.
-
E.
Kuala Kangsar
Kuala Kangsar is a historic royal town in the Malaysian state of Perak, known as the traditional seat of the Perak Sultanate.
- 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_69c69f2696688190915a8458f2398211 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5b32c708190bb3a92d0d949304a |
completed | March 27, 2026, 9:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83c9953e88190a1e0e899f2ddf822 |
completed | March 28, 2026, 8:39 p.m. |
Created at: March 27, 2026, 3:44 p.m.