Triple
T629959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Celebes |
E15903
|
entity |
| Predicate | hasCity |
P316
|
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: [Celebes, hasCity, Makassar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Makassar Context triple: [Celebes, hasCity, 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.
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.
-
C.
Surabaya
Surabaya is Indonesia’s second-largest city and a key commercial and industrial hub on the island of Java, historically serving as one of the region’s most important seaports.
-
D.
Balikpapan
Balikpapan is a coastal city in East Kalimantan, Indonesia, known as a major oil and gas hub and one of the most developed urban centers on the island of Borneo.
-
E.
Samarinda
Samarinda is the capital and largest city of Indonesia’s East Kalimantan province on the island of Borneo, known as a key regional center for trade, industry, and river transport along the Mahakam River.
- 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ec051bc8190b3e3f8651a367d77 |
completed | March 1, 2026, 8:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a56eee035c8190868aeac32be57959 |
completed | March 2, 2026, 11:05 a.m. |
Created at: March 1, 2026, 7:35 p.m.