Triple
T20679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Chicago Fire of 1871 |
E410
|
entity |
| Predicate | areaBurned |
P175
|
FINISHED |
| Object | approximately 3.3 square miles |
—
|
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: approximately 3.3 square miles | Statement: [Great Chicago Fire of 1871, areaBurned, approximately 3.3 square miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaBurned Context triple: [Great Chicago Fire of 1871, areaBurned, approximately 3.3 square miles]
-
A.
deathTollEstimate
Indicates an estimated number of deaths attributed to a particular event, cause, or period.
-
B.
casualtiesEstimate
Indicates an estimated number of people killed, injured, or otherwise harmed as a result of an event or incident.
-
C.
landArea
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
-
D.
damagedBy
Indicates that one entity has caused harm, impairment, or deterioration to another entity.
-
E.
area
chosen
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
- 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a246f7bd30819085f751c41f6f029e |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246526f5881909bc2a46e978bd082 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.