Triple
T11516099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wapama |
E273033
|
entity |
| Predicate | reasonForDismantling |
P13074
|
FINISHED |
| Object | severe structural deterioration |
—
|
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: severe structural deterioration | Statement: [Wapama, reasonForDismantling, severe structural deterioration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForDismantling Context triple: [Wapama, reasonForDismantling, severe structural deterioration]
-
A.
reasonForDemolition
chosen
Indicates the cause, justification, or circumstance that led to a structure or object being demolished.
-
B.
aimedToBeDismantledBy
Indicates that one entity was the intended target of dismantling or disassembly by another entity.
-
C.
purposeOfDestruction
Indicates that something is destroyed with the specific aim or intention of achieving a particular goal or outcome.
-
D.
hasCauseOfDestruction
Indicates that one entity is the cause or agent responsible for the destruction or damage of another entity.
-
E.
dismantledIn
Indicates that an entity was taken apart, disassembled, or broken down within a specified context, such as a particular time, place, or event.
- 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_69d6aae2c3748190bed2ea50dfb160dc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d87fcc72a48190b81acedfcc8685d3 |
completed | April 10, 2026, 4:42 a.m. |
| PD | Predicate disambiguation | batch_69d80876e5f0819088cff2e72f773cf6 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:36 p.m.