Triple
T17851920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ichikawa |
E445827
|
entity |
| Predicate | hasSisterCity |
P919
|
FINISHED |
| Object | Medan, Indonesia |
—
|
NE NERFINISHED |
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: Medan, Indonesia | Statement: [Ichikawa, hasSisterCity, Medan, Indonesia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Medan, Indonesia Context triple: [Ichikawa, hasSisterCity, Medan, Indonesia]
-
A.
Medan
chosen
Medan is a major economic and cultural hub in northern Sumatra, known as one of Indonesia’s largest cities and a gateway to the region.
-
B.
Medan
Medan is a minor biblical figure mentioned in the Book of Genesis as one of the sons of Abraham by his wife Keturah.
-
C.
Sabang
Sabang is a small Indonesian city and popular tourist destination located on Weh Island off the northern tip of Sumatra.
-
D.
Sabang
Sabang is a coastal barangay in Baler, Aurora, Philippines, known for its surfing beaches and tourism.
-
E.
Sabang
Sabang is a barangay (village-level administrative division) located in the municipality of Morong in the province of Bataan, Philippines.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48fff6c288190a2b5e60b66c03ddc |
completed | April 19, 2026, 8:19 a.m. |
Created at: April 10, 2026, 10:17 a.m.