Triple
T29200637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Venray |
E740260
|
entity |
| Predicate | wasLiberatedIn |
P14067
|
FINISHED |
| Object | 1944 |
—
|
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: 1944 | Statement: [Venray, wasLiberatedIn, 1944]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasLiberatedIn Context triple: [Venray, wasLiberatedIn, 1944]
-
A.
liberationDate
chosen
Indicates the date on which an entity was freed, released, or liberated from a prior state of control, confinement, or oppression.
-
B.
countryLiberated
Indicates that one country has freed another country from occupation, control, or oppression, restoring its independence or autonomy.
-
C.
wasFirstMajorTownLiberatedIn
Indicates that one entity was the first major town to be liberated in the context of a specified event or conflict.
-
D.
liberatedArea
Indicates that a particular area has been freed from control, occupation, or domination by a previously prevailing power or force.
-
E.
liberationPlace
Indicates the place or location where an entity was liberated or set free.
- 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_69f07cb974108190b7e86ca489a6ebb6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f663c58d2081909091380f074097be |
completed | May 2, 2026, 8:51 p.m. |
| PD | Predicate disambiguation | batch_69f65c24f8b48190af81b575f3c15be5 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 12:06 p.m.