Triple
T3516485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orinoco Belt |
E74319
|
entity |
| Predicate | viscosity |
P48486
|
FINISHED |
| Object | very high viscosity crude |
—
|
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: very high viscosity crude | Statement: [Orinoco Belt, viscosity, very high viscosity crude]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viscosity Context triple: [Orinoco Belt, viscosity, very high viscosity crude]
-
A.
dragCoefficient
Indicates the dimensionless proportionality factor that relates the drag force experienced by an object moving through a fluid to its shape, flow conditions, and reference area.
-
B.
porosity
Indicates the degree to which a material or structure contains voids or pores relative to its total volume.
-
C.
hardness
Indicates the degree to which one entity resists being scratched, indented, or deformed by another.
-
D.
thickness
Indicates the measure of how deep or wide an object or layer is from one surface or side to its opposite.
-
E.
concentration
Indicates the degree to which a substance or entity is present within a given medium, mixture, or space.
- 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_69ad85cfb5c881909c9a2edd9d6043cc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc31c0688190a890621a901f5f5f |
completed | March 8, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69adae10689c8190b7dc6d7daa8295b6 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adaed74ecc8190b74dc70ab59a3e1c |
completed | March 8, 2026, 5:16 p.m. |
Created at: March 8, 2026, 3:19 p.m.