Triple
T7301467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Han River |
E167863
|
entity |
| Predicate | hasBridgeCount |
P20771
|
FINISHED |
| Object | more than 20 bridges in Seoul |
—
|
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: more than 20 bridges in Seoul | Statement: [Han River, hasBridgeCount, more than 20 bridges in Seoul]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBridgeCount Context triple: [Han River, hasBridgeCount, more than 20 bridges in Seoul]
-
A.
hasNumberOfBridges
chosen
Indicates the quantitative relationship specifying how many bridges are associated with a given entity.
-
B.
hasBridgeTo
Indicates that one entity is connected to another by a bridge or bridging structure that allows passage or linkage between them.
-
C.
hasBridges
Indicates that one entity possesses, contains, or is characterized by one or more bridges connecting locations or components.
-
D.
hasBridgeSection
Indicates that one entity includes or is associated with a specific bridge section as a distinct part or component.
-
E.
hasNumberOfMainBridges
Indicates the quantity of primary or main bridges associated with a given entity.
- 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_69c6888c820881909fc68f689fe1c251 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6ebb09164819099c4479d48c1688a |
completed | March 27, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69c6e76e67d88190bd3ca6864f45845a |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 3:01 p.m.