Triple
T28697724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gestapo in Warsaw |
E729459
|
entity |
| Predicate | hadOfficeAt |
P1268
|
FINISHED |
| Object | Aleja Szucha 25, Warsaw |
—
|
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: Aleja Szucha 25, Warsaw | Statement: [Gestapo in Warsaw, hadOfficeAt, Aleja Szucha 25, Warsaw]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadOfficeAt Context triple: [Gestapo in Warsaw, hadOfficeAt, Aleja Szucha 25, Warsaw]
-
A.
hadCompanyAt
Indicates that an entity was accompanied by or in the presence of another entity at a specific time or place.
-
B.
hasOffice
chosen
Indicates that an entity possesses or maintains an office at a particular location or within a specific organization.
-
C.
hasProperOffice
Indicates that an entity maintains an officially designated, appropriate office or place of business.
-
D.
hasAssociatedOffice
Indicates that an entity is linked to or connected with a particular office in an official or functional capacity.
-
E.
aboutOfficeHeld
Indicates that one entity is related to, or provides information about, a specific office or position that is or was held by 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_69f043e6e9688190b6bdd6e5665498ff |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f656b1d00c8190af5ce3a32a576ef9 |
completed | May 2, 2026, 7:55 p.m. |
| PD | Predicate disambiguation | batch_69f651ac855481908e30c3b345d31356 |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 28, 2026, 5:40 a.m.