Triple
T12153158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johor Bahru District |
E289507
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Pasir Gudang |
E216258
|
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: Pasir Gudang | Statement: [Johor Bahru District, contains, Pasir Gudang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pasir Gudang Context triple: [Johor Bahru District, contains, Pasir Gudang]
-
A.
Pasir Gudang
chosen
Pasir Gudang is an industrial port city in the state of Johor, Malaysia, known for its heavy industries and maritime activities along the Straits of Johor.
-
B.
Pasir Mas
Pasir Mas is a town in the Malaysian state of Kelantan, known as a local commercial and transport hub near the border with Thailand.
-
C.
Bandar Lengeh
Bandar Lengeh is a coastal city and important maritime port on the Persian Gulf in southern Iran’s Hormozgan Province.
-
D.
Pagar Alam
Pagar Alam is a highland city in southern Sumatra, Indonesia, known for its cool climate, tea plantations, and scenic mountain landscapes near Mount Dempo.
-
E.
Pelabuhan Ratu
Pelabuhan Ratu is a coastal town and bay in West Java, Indonesia, known for its scenic beaches, strong surf, and local fishing culture.
- 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915bf615c8190ad5f8ae8665678dc |
completed | April 10, 2026, 3:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f69aa2e88190aaa58468571d6dad |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:49 p.m.