Triple
T1982028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Comandancia in Panama City |
E43047
|
entity |
| Predicate | impactOnArea |
P1586
|
FINISHED |
| Object | its destruction contributed to heavy damage in El Chorrillo |
—
|
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: its destruction contributed to heavy damage in El Chorrillo | Statement: [Comandancia in Panama City, impactOnArea, its destruction contributed to heavy damage in El Chorrillo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: impactOnArea Context triple: [Comandancia in Panama City, impactOnArea, its destruction contributed to heavy damage in El Chorrillo]
-
A.
affectedArea
chosen
Indicates the specific region or extent over which an event, condition, or influence has an impact.
-
B.
impactRegion
Indicates the geographic or spatial area that is affected or influenced by a particular event, action, or phenomenon.
-
C.
impactBuilding
Indicates that one entity physically collides with or strikes a building, causing an impact event.
-
D.
area
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
E.
impactIfCompleted
Indicates the effect or consequence that will occur if the referenced task or action is fully completed.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb96f932881908bebfc4176fda7c0 |
completed | March 7, 2026, 5:36 a.m. |
| PD | Predicate disambiguation | batch_69abb798d288819083132cf14605bd02 |
completed | March 7, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:37 p.m.