Triple
T603390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Blitz |
E11542
|
entity |
| Predicate | numberOfHomesDestroyed |
P1583
|
FINISHED |
| Object | over 1,000,000 homes damaged or destroyed |
—
|
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: over 1,000,000 homes damaged or destroyed | Statement: [The Blitz, numberOfHomesDestroyed, over 1,000,000 homes damaged or destroyed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfHomesDestroyed Context triple: [The Blitz, numberOfHomesDestroyed, over 1,000,000 homes damaged or destroyed]
-
A.
buildingsDestroyed
chosen
Indicates that one or more buildings have been damaged to the point of destruction as a result of some event or action.
-
B.
mainCityDestroyed
Indicates that the primary or central city associated with an entity has been destroyed.
-
C.
numberOfEvacuated
Indicates the total count of individuals who have been evacuated from a location or situation.
-
D.
hasCauseOfDestruction
Indicates that one entity is the cause or agent responsible for the destruction or damage of another entity.
-
E.
estimatedNumberOfPeopleSaved
Indicates the approximate count of individuals whose lives were preserved or harm was averted as a result of a particular action, intervention, or 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_69a4932779b881908688590d59c71900 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49e574444819087999404f3e3ffd9 |
completed | March 1, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69a49cf701e08190966d06b9ff4b582b |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.