Triple
T7829878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hashem Abedi |
E181338
|
entity |
| Predicate | victimsNumber |
P63692
|
FINISHED |
| Object | 22 fatalities in Manchester Arena bombing |
—
|
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: 22 fatalities in Manchester Arena bombing | Statement: [Hashem Abedi, victimsNumber, 22 fatalities in Manchester Arena bombing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimsNumber Context triple: [Hashem Abedi, victimsNumber, 22 fatalities in Manchester Arena bombing]
-
A.
numberOfVictimsClaimed
Indicates the reported count of victims associated with a particular event, incident, or action.
-
B.
numberOfVictimsKilled
chosen
Indicates the count of victims who were killed as a result of the referenced event or action.
-
C.
numberOfSuspectedVictims
Indicates the count of individuals believed or alleged to be victims in a particular incident, case, or context.
-
D.
numberOfVictimsInjured
Indicates the count of victims who sustained injuries as a result of the event or incident.
-
E.
numberOfTortureVictims
Indicates the quantity of individuals who have been subjected to torture.
- 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_69ca8282ccec819083c48efb72d21cf9 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb04ac013c81909533fa348776f50c |
completed | March 30, 2026, 11:18 p.m. |
| PD | Predicate disambiguation | batch_69cae91ae008819098e56bbe51143b31 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:44 p.m.