Triple
T27714723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin-Gropius-Bau |
E698782
|
entity |
| Predicate | nearBuilding |
P61362
|
FINISHED |
| Object | Topography of Terror documentation center |
—
|
NE NERFINISHED |
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: Topography of Terror documentation center | Statement: [Martin-Gropius-Bau, nearBuilding, Topography of Terror documentation center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearBuilding Context triple: [Martin-Gropius-Bau, nearBuilding, Topography of Terror documentation center]
-
A.
builtNear
Indicates that one entity was constructed at a location geographically close to another entity.
-
B.
near
Indicates that one entity is located at a short distance from another entity in space or position.
-
C.
hasMainBuildingNear
Indicates that the primary or central building associated with an entity is located in close physical proximity to another specified entity or place.
-
D.
meetsNear
Indicates that two entities meet or come together at a location that is in close proximity to a specified reference point or area.
-
E.
nearbyTo
chosen
Indicates that one entity is located close in distance or position to another entity.
- 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_69ef590f655c81909f93893b3b3219b2 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f7688dd3d08190ad13d0e780570a1c |
completed | May 3, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69f767fcf2f881908bacc7bfc38e68a5 |
completed | May 3, 2026, 3:21 p.m. |
Created at: April 27, 2026, 3:04 p.m.