Triple
T15566197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louis Dreyfus Company |
E371120
|
entity |
| Predicate | operatesFacilitiesIn |
P26656
|
FINISHED |
| Object | over 100 countries |
—
|
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: over 100 countries | Statement: [Louis Dreyfus Company, operatesFacilitiesIn, over 100 countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatesFacilitiesIn Context triple: [Louis Dreyfus Company, operatesFacilitiesIn, over 100 countries]
-
A.
operatesFacility
Indicates that an entity is responsible for running, managing, or controlling the operations of a particular facility.
-
B.
hasFacilities
Indicates that an entity possesses, provides, or is equipped with certain facilities or physical resources.
-
C.
servesFacility
Indicates that one entity provides services or support to a particular facility as its client, target, or area of operation.
-
D.
alsoOperatesIn
chosen
Indicates that an entity, in addition to its primary location or domain, conducts operations or activities in another specified place or context.
-
E.
operatedAmong
Indicates that an entity carried out operations or activities within, or in coordination with, a specified group, set, or collection of other entities.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ddd753c8190b51eaef433258081 |
completed | April 16, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69deda7e6e748190b29ccce23298afef |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:10 a.m.