Triple
T3950300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cocoa House |
E84848
|
entity |
| Predicate | materialSource |
P53073
|
FINISHED |
| Object | cocoa revenue |
—
|
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: cocoa revenue | Statement: [Cocoa House, materialSource, cocoa revenue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: materialSource Context triple: [Cocoa House, materialSource, cocoa revenue]
-
A.
sourceMaterialType
Indicates the type or category of material from which something originates or is derived.
-
B.
hasSourceMaterial
Indicates that something is derived from, based on, or created using a particular source material.
-
C.
material
Indicates that one entity is physically composed of, made from, or constructed using the substance or material represented by the other entity.
-
D.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
E.
featuresMaterialFrom
Indicates that one entity incorporates, contains, or is composed of material originating from another entity.
- 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_69aed934fbfc8190847068e4546de963 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaa5afdc8190b709af2473d75d02 |
completed | March 9, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69aef8ed04e4819096bced8971cd888d |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefaa3c6a08190bfe76629c7c98eea |
completed | March 9, 2026, 4:51 p.m. |
Created at: March 9, 2026, 3:30 p.m.