Triple
T5330972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hunger Winter |
E123306
|
entity |
| Predicate | mainlyAffects |
P25489
|
FINISHED |
| Object | civilian population of the western Netherlands |
—
|
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: civilian population of the western Netherlands | Statement: [Hunger Winter, mainlyAffects, civilian population of the western Netherlands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainlyAffects Context triple: [Hunger Winter, mainlyAffects, civilian population of the western Netherlands]
-
A.
appliesPrimarilyTo
Indicates that a property, rule, or characteristic is mainly relevant or intended for a particular entity or group, more than for others.
-
B.
areAffectedBy
chosen
Indicates that one entity experiences an effect, influence, or impact as a result of another entity or event.
-
C.
primaryEffect
Indicates the main direct outcome or consequence that results from a given cause, action, or condition.
-
D.
frontAffected
Indicates that an action, event, or condition primarily impacts the front side or front-facing part of an entity.
-
E.
affectsProgram
Indicates that one entity produces an influence or change on a program, altering its behavior, state, or outcome.
- 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_69bd46477f9081909d242a327d749466 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85969cc88190a3a5efbab7d9fe86 |
completed | March 20, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69bd84583dbc819088a03e3afb30178c |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2 p.m.