Triple
T1512432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antwerp |
E32042
|
entity |
| Predicate | portRankInEuropeByTonnage |
P15920
|
FINISHED |
| Object | among largest seaports |
—
|
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: among largest seaports | Statement: [Antwerp, portRankInEuropeByTonnage, among largest seaports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portRankInEuropeByTonnage Context triple: [Antwerp, portRankInEuropeByTonnage, among largest seaports]
-
A.
passengerTrafficRankInEurope
Indicates the relative position of an entity in Europe based on the volume of passenger traffic it handles.
-
B.
cargoTrafficRankInEurope
chosen
Indicates the relative position of an entity in terms of cargo traffic volume compared to other entities within Europe.
-
C.
portRank
Indicates the relative importance or hierarchical ranking assigned to a port within a given system or context.
-
D.
maritimeGatewayFor
Indicates a relationship where one location serves as the primary seaport or ocean-access point enabling maritime connectivity and trade for another location.
-
E.
rankByLengthInEurope
Indicates that entities are ordered or compared based on their length specifically within the context of Europe.
- 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_69a885e8caf88190a5fbb6159ce87786 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9396e16408190b5e7b0ac43376d81 |
completed | March 5, 2026, 8:06 a.m. |
| PD | Predicate disambiguation | batch_69a907aa67cc81909f00135365447399 |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.