Triple
T25542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Livadia Palace |
E510
|
entity |
| Predicate | predecessorDestroyed |
P1512
|
FINISHED |
| Object | demolished in early 20th century |
—
|
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: demolished in early 20th century | Statement: [Livadia Palace, predecessorDestroyed, demolished in early 20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: predecessorDestroyed Context triple: [Livadia Palace, predecessorDestroyed, demolished in early 20th century]
-
A.
predecessor
Indicates that one entity comes before another in an ordered sequence or succession.
-
B.
wasSupersededBy
Indicates that one entity has been replaced or made obsolete by another entity that takes over its role or function.
-
C.
successor
Indicates that one entity directly follows another in an ordered sequence or position.
-
D.
reconstructedAfter
Indicates that one entity has been rebuilt, restored, or reassembled following the occurrence or existence of another entity or event.
-
E.
hasAncestor
Indicates that one entity is an ancestor (direct or indirect, such as a parent, grandparent, etc.) of another entity in a genealogical or hierarchical lineage.
- F. None of above. chosen
Provenance (4 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246d794448190bb2844fcd0538eaa |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a24657635881908f3415bc1bdfa1b5 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a246d6aca88190a86b7c41d497bacd |
completed | Feb. 28, 2026, 1:37 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.