Triple
T5974811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soekarno-Hatta Port |
E132959
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Makassar |
E23614
|
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: Makassar | Statement: [Soekarno-Hatta Port, locatedIn, Makassar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Makassar Context triple: [Soekarno-Hatta Port, locatedIn, Makassar]
-
A.
Makassar
chosen
Makassar is a major port city on the southwest coast of Sulawesi known historically as a key maritime trading hub in eastern Indonesia.
-
B.
Kendari
Kendari is the capital and largest city of Southeast Sulawesi Province on the Indonesian island of Sulawesi, known as a regional center for trade and maritime activities.
-
C.
Palu
Palu is a coastal city on the Indonesian island of Sulawesi, known as the capital of Central Sulawesi province and a regional center for trade and administration.
-
D.
Banjarmasin
Banjarmasin is a major riverine city in South Kalimantan, Indonesia, known for its historic floating markets and strategic location on the island of Borneo.
-
E.
Palopo
Palopo is a coastal city in Indonesia known as an important regional center in the province of South Sulawesi.
- 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_69c0086deab081908550159ca23eec9b |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04a39c9d08190a78e1e3268584eb5 |
completed | March 22, 2026, 7:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c63849a59881909e32c0271b4beb51 |
completed | March 27, 2026, 7:56 a.m. |
Created at: March 22, 2026, 4:03 p.m.