Triple
T9257666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aramco Trading Company |
E222485
|
entity |
| Predicate | hasTradingDesk |
P87830
|
FINISHED |
| Object | Crude oil trading desk |
—
|
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: Crude oil trading desk | Statement: [Aramco Trading Company, hasTradingDesk, Crude oil trading desk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTradingDesk Context triple: [Aramco Trading Company, hasTradingDesk, Crude oil trading desk]
-
A.
hasTradingFloor
Indicates that an entity operates or contains a physical or virtual trading floor where financial instruments are actively bought and sold.
-
B.
hasTradingVenueType
Indicates the specific category or type of trading venue associated with a given trading platform or marketplace.
-
C.
hasTradingVenueCode
Indicates that an entity is associated with a specific trading venue through its designated code.
-
D.
hasTradingModel
Indicates that one entity uses, is governed by, or is associated with a particular trading model.
-
E.
hasMarketMakers
Indicates that an entity is associated with one or more market makers who provide liquidity or facilitate trading for it.
- 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_69ca841e4cd481908e738c74e958eaea |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd06b660448190b6bc04beff0f5512 |
completed | April 1, 2026, 11:51 a.m. |
| PD | Predicate disambiguation | batch_69cc7a4e79e48190b3200247f4624867 |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc95597be081908ece2491dd2f0f74 |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:32 p.m.