Triple
T2175938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World Red Cross and Red Crescent Day |
E48527
|
entity |
| Predicate | themeType |
P20708
|
FINISHED |
| Object | humanitarianism |
—
|
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: humanitarianism | Statement: [World Red Cross and Red Crescent Day, themeType, humanitarianism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: themeType Context triple: [World Red Cross and Red Crescent Day, themeType, humanitarianism]
-
A.
themeFor
Indicates that something serves as the central subject, topic, or focus for another thing (such as an event, work, or activity).
-
B.
theme
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
-
C.
themeExamples
Indicates that the related entity serves as an example or illustration of the theme expressed by the subject.
-
D.
themeContrast
Indicates a relationship where two themes are compared or opposed to highlight their differences or tension.
-
E.
themedAs
chosen
Indicates that something is characterized, styled, or organized according to a particular theme or motif.
- 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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc4358fc88190a6f556c2de9fef8c |
completed | March 7, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69abbda0ec948190be88c1243d81a423 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:45 p.m.