Triple
T23948478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Matadi |
E602976
|
entity |
| Predicate | distanceFromMouthOfCongoRiver |
P55788
|
FINISHED |
| Object | approximately 150 kilometers |
—
|
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: approximately 150 kilometers | Statement: [Port of Matadi, distanceFromMouthOfCongoRiver, approximately 150 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMouthOfCongoRiver Context triple: [Port of Matadi, distanceFromMouthOfCongoRiver, approximately 150 kilometers]
-
A.
distanceToKinshasa
Indicates the measured spatial distance between a given entity’s location and the city of Kinshasa.
-
B.
distanceFromVictoriaFalls
Indicates the measured distance between a given location and Victoria Falls.
-
C.
distanceFromAtlanticMouthOfAmazon
Indicates the measured distance of something from the point where the Amazon River meets the Atlantic Ocean.
-
D.
distanceFromNile
Indicates the spatial distance between a given location or entity and the Nile River.
-
E.
riverMileFromMouth
chosen
Indicates the distance, measured in river miles, from the river’s mouth upstream to a specific point along the river.
- 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_69e2953e4924819093f1c24c03476b42 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d03067348190a2cccb809ebdc0ad |
completed | April 29, 2026, 9:32 a.m. |
| PD | Predicate disambiguation | batch_69f1615518088190a206f54e2fdb14a3 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:18 p.m.