Triple
T2536620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Management |
E56282
|
entity |
| Predicate | hadScope |
P397
|
FINISHED |
| Object | global operations of the United Nations |
—
|
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: global operations of the United Nations | Statement: [Department of Management, hadScope, global operations of the United Nations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadScope Context triple: [Department of Management, hadScope, global operations of the United Nations]
-
A.
hasSee
Indicates that one entity has perceived or visually observed another entity.
-
B.
hasScope
chosen
Indicates that one entity defines, limits, or encompasses the range, extent, or applicability within which another entity operates or is valid.
-
C.
has
Indicates that one entity possesses, owns, contains, or includes another entity as part of its state or composition.
-
D.
hadNo
Indicates that one entity completely lacked or did not possess another entity, attribute, or relationship.
-
E.
hadOrgan
Indicates that an entity previously possessed or contained a specific organ as part of its body.
- 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_69ab4a49b6508190bc467fbef4bac334 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd64a2194819097c66cbeb37fe859 |
completed | March 7, 2026, 7:39 a.m. |
| PD | Predicate disambiguation | batch_69abd0c4a5dc819097812db50443420a |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:47 p.m.