Triple
T11969060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quinta del Sordo |
E284867
|
entity |
| Predicate | demolitionRelatedTo |
P35276
|
FINISHED |
| Object | urban development near Madrid |
—
|
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: urban development near Madrid | Statement: [Quinta del Sordo, demolitionRelatedTo, urban development near Madrid]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: demolitionRelatedTo Context triple: [Quinta del Sordo, demolitionRelatedTo, urban development near Madrid]
-
A.
hasDemolitionOrDestruction
chosen
Indicates that one entity causes, undergoes, or is associated with the demolition or destruction of another entity.
-
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.
demolishedWith
Indicates that one entity was destroyed or torn down using another specified tool, method, or agent.
-
D.
demolishedOrDestroyed
Indicates that one entity has caused another entity to be torn down, ruined, or rendered unusable, typically through deliberate demolition or destructive force.
-
E.
demolitionMethod
Indicates the technique or process used to carry out a demolition.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9037bee54819085242a3ef3e286f9 |
completed | April 10, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69d8bb40f30c8190a0e0719bd67542bf |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:46 p.m.