Triple
T7543353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lubyanka Square, Moscow |
E178334
|
entity |
| Predicate | hasMonumentHistory |
P1098
|
FINISHED |
| Object | site of a statue of Felix Dzerzhinsky until 1991 |
—
|
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: site of a statue of Felix Dzerzhinsky until 1991 | Statement: [Lubyanka Square, Moscow, hasMonumentHistory, site of a statue of Felix Dzerzhinsky until 1991]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMonumentHistory Context triple: [Lubyanka Square, Moscow, hasMonumentHistory, site of a statue of Felix Dzerzhinsky until 1991]
-
A.
hasNumberOfMonuments
Indicates the specific count of monuments associated with or present in a given entity.
-
B.
hasHistoricSite
chosen
Indicates that an entity possesses, contains, or is associated with a place recognized for its historical significance.
-
C.
hasWorkOnMonument
Indicates that an entity has created, contributed to, or performed work on a particular monument.
-
D.
hasRomanMonument
Indicates that one entity possesses, contains, or includes a monument of Roman origin or style.
-
E.
hasHistoricalSignificance
Indicates that something possesses notable importance or influence within a historical context or period.
- 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_69c69f2be3888190a6667a27f8f195e9 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f896a27481908b2e120208f268e7 |
completed | March 27, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69c6f4daad6c8190af2b8ae88d2c8cb7 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:48 p.m.