Triple
T13449791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clydebank Blitz |
E320577
|
entity |
| Predicate | civilianInjuries |
P34803
|
FINISHED |
| Object | thousands |
—
|
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: thousands | Statement: [Clydebank Blitz, civilianInjuries, thousands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: civilianInjuries Context triple: [Clydebank Blitz, civilianInjuries, thousands]
-
A.
civilianImpact
Indicates the extent to which an action, event, or situation affects civilians, especially in terms of harm, disruption, or other consequences.
-
B.
casualtiesCiviliansWounded
chosen
Indicates that an event or action resulted in civilian individuals being wounded or injured.
-
C.
casualtiesCiviliansKilled
Indicates that the relationship records the number of civilian deaths resulting from a specific event or action.
-
D.
primaryCasualtiesFrom
Indicates that an entity is the main source or cause of the casualties experienced by another entity.
-
E.
casualties
Indicates that an event, action, or situation resulted in people being killed or injured.
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaef973b08190a3d7fe1c2a913cff |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03ce03481908c61094f0cc0c158 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:41 p.m.