Triple
T2856000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Invalidenfriedhof |
E63200
|
entity |
| Predicate | partlyDestroyedBy |
P23714
|
FINISHED |
| Object | construction of the Berlin Wall |
—
|
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: construction of the Berlin Wall | Statement: [Invalidenfriedhof, partlyDestroyedBy, construction of the Berlin Wall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partlyDestroyedBy Context triple: [Invalidenfriedhof, partlyDestroyedBy, construction of the Berlin Wall]
-
A.
partiallyDestroyed
chosen
Indicates that an entity has been damaged or ruined to a significant extent but not completely destroyed.
-
B.
damagedBy
Indicates that one entity has caused harm, impairment, or deterioration to another entity.
-
C.
hasCauseOfDestruction
Indicates that one entity is the cause or agent responsible for the destruction or damage of another entity.
-
D.
sufferedDestructionIn
Indicates that an entity experienced damage, ruin, or devastation during or as part of a specified event or period.
-
E.
areaDestroyed
Indicates that a specified portion or region has been damaged or ruined to the point of destruction.
- 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_69ab4c41e8c08190a9e8f5249cc12610 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf62308081908a65decdd5d6f918 |
completed | March 7, 2026, 8:18 a.m. |
| PD | Predicate disambiguation | batch_69abdd10aef88190b750aae07e7df4dc |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:02 p.m.