Triple
T31580929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Europe, Middle East and Africa |
E805820
|
entity |
| Predicate | labelUsedIn |
P45202
|
FINISHED |
| Object | corporate organizational charts |
—
|
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: corporate organizational charts | Statement: [Europe, Middle East and Africa, labelUsedIn, corporate organizational charts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: labelUsedIn Context triple: [Europe, Middle East and Africa, labelUsedIn, corporate organizational charts]
-
A.
usedInLabeling
chosen
Indicates that something is employed or applied as part of a labeling process or activity.
-
B.
usedLabel
Indicates that one entity has applied, assigned, or referenced a particular label to another entity or resource.
-
C.
designationUsedFor
Indicates that a particular name, label, or title is employed to refer to or identify a specific entity or role.
-
D.
areUsedIn
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
-
E.
brandNameUsedIn
Indicates that a particular brand name is used or appears within a specified context, such as a product, document, or communication.
- 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_69f348d3a86c8190a3e5e539a4dd125f |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6abaa1f648190b77073771df3bf3b |
completed | May 3, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69f6aa1e84b88190b025f6ca40f17a8a |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 10:23 p.m.