Triple
T9127201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Člověk v tísni |
E218994
|
entity |
| Predicate | worksInArea |
P23945
|
FINISHED |
| Object | crisis regions |
—
|
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: crisis regions | Statement: [Člověk v tísni, worksInArea, crisis regions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worksInArea Context triple: [Člověk v tísni, worksInArea, crisis regions]
-
A.
worksWith
Indicates that two entities collaborate or perform tasks together in a shared work-related context.
-
B.
hasWorksLocatedIn
Indicates that the works or creations associated with an entity are situated or stored in a specified location.
-
C.
worksFor
Indicates that one entity is employed by or performs work on behalf of another entity, typically an organization or individual.
-
D.
mayWorkIn
Indicates that an entity is allowed or has the possibility to work in a particular place, organization, or context.
-
E.
notableWorkArea
chosen
Indicates the field or domain in which an entity’s significant work or contributions are primarily focused.
- 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_69ca83debfc0819095800583e97ab10f |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8c93d3c8190b003b2b1af2003b2 |
completed | April 1, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69cc66003e3c819091e1e42c9cf7c781 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:18 p.m.