Triple
T1602456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2017 Manchester Arena bombing |
E34424
|
entity |
| Predicate | deadliestIn |
P30647
|
FINISHED |
| Object | United Kingdom since 7 July 2005 London bombings |
—
|
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: United Kingdom since 7 July 2005 London bombings | Statement: [2017 Manchester Arena bombing, deadliestIn, United Kingdom since 7 July 2005 London bombings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: deadliestIn Context triple: [2017 Manchester Arena bombing, deadliestIn, United Kingdom since 7 July 2005 London bombings]
-
A.
deathToll
Indicates the number of deaths resulting from a particular event, situation, or cause.
-
B.
deathApprox
Indicates that an entity’s death occurred at an approximate, rather than exact, time or date.
-
C.
fatalitiesCategory
Indicates the classification of deaths associated with an event, incident, or condition into a specific category or severity level.
-
D.
deathDescribedIn
Indicates that a person's death is documented, narrated, or otherwise detailed within a particular source or description.
-
E.
causeOfDeath
Indicates the specific factor, event, or condition that directly resulted in an entity’s death.
- F. None of above. chosen
Provenance (4 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_69a885fea6a481909fe83ba6441f1774 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a95b02cd448190be8e3db9a5a7bac0 |
completed | March 5, 2026, 10:29 a.m. |
| PD | Predicate disambiguation | batch_69a907c1cad08190b9728dd557f39aa0 |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a95aada3f881909053363c01de8b57 |
completed | March 5, 2026, 10:29 a.m. |
Created at: March 4, 2026, 7:28 p.m.