Triple
T3550022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buckingham House |
E75087
|
entity |
| Predicate | demolishedOrAbsorbed |
P50531
|
FINISHED |
| Object | 19th 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: 19th century | Statement: [Buckingham House, demolishedOrAbsorbed, 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: demolishedOrAbsorbed Context triple: [Buckingham House, demolishedOrAbsorbed, 19th century]
-
A.
demolishedWith
Indicates that one entity was destroyed or torn down using another specified tool, method, or agent.
-
B.
demolished
Indicates that one entity completely destroyed or razed another entity, typically a structure or object, so that it no longer exists in its previous form.
-
C.
hasDemolitionOrDestruction
Indicates that one entity causes, undergoes, or is associated with the demolition or destruction of another entity.
-
D.
demolishedOriginalStructures
Indicates that one entity has completely destroyed or removed the original structures associated with another entity.
-
E.
demolishedToMakeWayFor
Indicates that one entity was intentionally destroyed or removed in order to create space for another entity or development.
- 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_69ad85d33c6c819081d5ac1df13b5680 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbfd38c8c8190a4591689ad57c998 |
completed | March 8, 2026, 6:28 p.m. |
| PD | Predicate disambiguation | batch_69adb83270ac819083967db0570167d2 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adba25c66c81909a05a97327828c41 |
completed | March 8, 2026, 6:04 p.m. |
Created at: March 8, 2026, 3:20 p.m.