Triple
T24090457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hasib Hussain |
E596771
|
entity |
| Predicate | attackInjuredCountContext |
P63693
|
FINISHED |
| Object | over 700 people injured in the 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: over 700 people injured in the 7 July 2005 London bombings | Statement: [Hasib Hussain, attackInjuredCountContext, over 700 people injured in the 7 July 2005 London bombings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attackInjuredCountContext Context triple: [Hasib Hussain, attackInjuredCountContext, over 700 people injured in the 7 July 2005 London bombings]
-
A.
injuredIn
Indicates that an entity sustained an injury as a result of a specified event, situation, or action.
-
B.
numberOfVictimsInjured
chosen
Indicates the count of victims who sustained injuries as a result of the event or incident.
-
C.
hasInjuredPerson
Indicates that an entity has a person who has been harmed or injured associated with it.
-
D.
injuryStatus
Indicates the condition or state of harm, damage, or physical injury affecting an entity.
-
E.
hasInjuries
Indicates that an entity has sustained one or more physical or bodily injuries.
- 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.