Triple
T24090456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hasib Hussain |
E596771
|
entity |
| Predicate | victimCountContext |
P63692
|
FINISHED |
| Object | 52 people killed in the 7 July 2005 London bombings (excluding bombers) |
—
|
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: 52 people killed in the 7 July 2005 London bombings (excluding bombers) | Statement: [Hasib Hussain, victimCountContext, 52 people killed in the 7 July 2005 London bombings (excluding bombers)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: victimCountContext Context triple: [Hasib Hussain, victimCountContext, 52 people killed in the 7 July 2005 London bombings (excluding bombers)]
-
A.
numberOfVictimsKilled
chosen
Indicates the count of victims who were killed as a result of the referenced event or action.
-
B.
numberOfVictimsClaimed
Indicates the reported count of victims associated with a particular event, incident, or action.
-
C.
victimCountPolicy
Indicates the rule or criterion used to determine how victims are counted or classified in a given context.
-
D.
numberOfVictimsConfirmed
Indicates the confirmed count of victims associated with an event, incident, or situation.
-
E.
victimGroupContext
Indicates the contextual circumstances or setting in which a victim group is targeted, affected, or involved in an event or action.
- 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_69e288c4638c81909bacc28a1e3d436b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1dc2e672c8190b3e4be041835cc27 |
completed | April 29, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f17651458c8190bbfd301883e46085 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 10:51 p.m.