Triple
T24090431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hasib Hussain |
E596771
|
entity |
| Predicate | numberOfCoPerpetrators |
P155042
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Hasib Hussain, numberOfCoPerpetrators, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCoPerpetrators Context triple: [Hasib Hussain, numberOfCoPerpetrators, 3]
-
A.
numberOfPerpetrators
Indicates the count of distinct individuals who carried out or participated in a particular act, event, or offense.
-
B.
numberOfPerpetratorsKilled
Indicates the count of perpetrators who were killed in the context of the described event or incident.
-
C.
hasPerpetrators
Indicates that certain entities are responsible for carrying out, committing, or executing a particular act, event, or wrongdoing.
-
D.
numberOfPeopleAccused
Indicates the count of individuals who are formally alleged to have committed a particular act or offense.
-
E.
partnerInCrime
Indicates a relationship where two or more entities collaborate closely in committing or planning wrongful, illicit, or mischievous acts together.
- 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_69e288c4638c81909bacc28a1e3d436b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1dc2d405881909469aa95901ab87b |
completed | April 29, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f17651458c8190bbfd301883e46085 |
completed | April 29, 2026, 3:09 a.m. |
| PDg | Predicate description generation | batch_69f17b58012c81909106b332db399023 |
completed | April 29, 2026, 3:30 a.m. |
Created at: April 17, 2026, 10:51 p.m.