Triple
T18979005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeju Province |
E464371
|
entity |
| Predicate | hasAreaRankInSouthKorea |
P1170
|
FINISHED |
| Object | smallest among provinces |
—
|
LITERAL 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: smallest among provinces | Statement: [Jeju Province, hasAreaRankInSouthKorea, smallest among provinces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAreaRankInSouthKorea Context triple: [Jeju Province, hasAreaRankInSouthKorea, smallest among provinces]
-
A.
hasAreaRankInTaiwan
Indicates the relative ranking of an entity by its area size compared to other entities within Taiwan.
-
B.
rankInChinaByArea
Indicates the position of an entity in an ordered list of entities in China when sorted by their area size.
-
C.
areaRank
chosen
Indicates the relative ordering or position of an entity based on the size of its area compared to others.
-
D.
regionRankContext
Indicates the relative ranking or position of something within a specific geographic or regional context.
-
E.
areaRankingInJapan
Indicates the relative position of an entity in a size-based ranking within Japan.
- F. None of above.
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_69d8dd008af48190a97ff1c6488edf1b |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d621e3e08190b2d1d969ecaa380b |
completed | April 20, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69e4a2f437648190b85650dae8885d48 |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:01 p.m.