Triple
T4772098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tannenberg Memorial |
E105950
|
entity |
| Predicate | successorMemorial |
P37170
|
FINISHED |
| Object | local World War I memorials near Olsztynek |
—
|
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: local World War I memorials near Olsztynek | Statement: [Tannenberg Memorial, successorMemorial, local World War I memorials near Olsztynek]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: successorMemorial Context triple: [Tannenberg Memorial, successorMemorial, local World War I memorials near Olsztynek]
-
A.
successorMonument
chosen
Indicates that one monument replaces, follows, or is designated as the subsequent monument to another in a sequence or historical succession.
-
B.
successorNamesake
Indicates that one entity is named after another entity that precedes it, typically as its successor or continuation in name.
-
C.
successor
Indicates that one entity directly follows another in an ordered sequence or position.
-
D.
hasMemorial
Indicates that a memorial exists in honor of, or dedicated to, a particular entity.
-
E.
memorialName
Indicates that a memorial is known by or designated with a particular name.
- 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_69bd43f226fc8190b867cc249c2a9042 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd655e5dcc8190a932be9b1baaffb2 |
completed | March 20, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69bd6229d8448190a271719e5e30fd82 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:21 p.m.