Triple
T788259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mekong River |
E16852
|
entity |
| Predicate | rankByLengthInWorld |
P19300
|
FINISHED |
| Object | among the world’s longest rivers |
—
|
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 the world’s longest rivers | Statement: [Mekong River, rankByLengthInWorld, among the world’s longest rivers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByLengthInWorld Context triple: [Mekong River, rankByLengthInWorld, among the world’s longest rivers]
-
A.
rankByLength
Indicates ordering a set of items based on their length, typically from shortest to longest or vice versa.
-
B.
rankInWorldByArea
Indicates the position of an entity in a global ordering based on its total area size.
-
C.
rankByLengthInEurope
Indicates that entities are ordered or compared based on their length specifically within the context of Europe.
-
D.
rankByLengthInIndia
Indicates an ordering of items based on their length specifically within the context or boundaries of India.
-
E.
rankByHeightWorld
Indicates an ordering of entities based on their relative height compared to all others in the world.
- F. None of above. chosen
Provenance (4 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a782fe988190966b958673fe12bf |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a50ef72c819084ffe9f31dbd0262 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a62b497081909503c8d30c7ce1db |
completed | March 1, 2026, 8:48 p.m. |
Created at: March 1, 2026, 7:38 p.m.