Triple
T22384821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lianjiang County |
E553367
|
entity |
| Predicate | hasMaritimeEconomy |
P76343
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Lianjiang County, hasMaritimeEconomy, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaritimeEconomy Context triple: [Lianjiang County, hasMaritimeEconomy, yes]
-
A.
hasMaritimeConnection
chosen
Indicates a relationship in which an entity is linked to seas, oceans, or maritime activities, such as shipping, navigation, or coastal operations.
-
B.
hasMajorSeaPort
Indicates that a place possesses at least one significant seaport used for major maritime transport, trade, or shipping activities.
-
C.
hasMaritimeHeritage
Indicates that an entity possesses a historical, cultural, or traditional connection to maritime activities, seafaring, or the sea.
-
D.
hasMarineResource
Indicates that one entity possesses, contains, or is associated with a marine (ocean or sea-based) resource in relation to another entity.
-
E.
hasMajorSeaLane
Indicates that a significant maritime shipping or navigation route passes through, borders, or is closely associated with the referenced 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_69e11e4cf87c8190a1ff474daec326b7 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1582e58dc8190a2ad6b10c9d1f951 |
completed | April 29, 2026, 1 a.m. |
| PD | Predicate disambiguation | batch_69e73015484c8190a9a0b9f554b61a81 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:45 p.m.