Triple
T27143278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Prawn |
E681870
|
entity |
| Predicate | riskOfDemolition |
P161892
|
FINISHED |
| Object | discussed before renovation |
—
|
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: discussed before renovation | Statement: [Big Prawn, riskOfDemolition, discussed before renovation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: riskOfDemolition Context triple: [Big Prawn, riskOfDemolition, discussed before renovation]
-
A.
hasDemolitionOrDestruction
Indicates that one entity causes, undergoes, or is associated with the demolition or destruction of another entity.
-
B.
demolitionImpact
Indicates the effect or consequences that a demolition action has on a target entity or its surrounding environment.
-
C.
reasonForDemolition
Indicates the cause, justification, or circumstance that led to a structure or object being demolished.
-
D.
demolitionOrDecline
Indicates that something is undergoing, has undergone, or is associated with either physical demolition or a process of decline.
-
E.
demolishedOrDestroyed
Indicates that one entity has caused another entity to be torn down, ruined, or rendered unusable, typically through deliberate demolition or destructive force.
- 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_69eefacca3888190b67238d380e8f28b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f624c3e4bc8190af9a5d9b3c30d117 |
completed | May 2, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69f61b40f02081909bd9c3ea73249163 |
completed | May 2, 2026, 3:41 p.m. |
| PDg | Predicate description generation | batch_69f61fa35ac48190890102c348ed81a0 |
completed | May 2, 2026, 4 p.m. |
Created at: April 27, 2026, 9:10 a.m.