Triple
T11426567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamza al-Ghamdi |
E270765
|
entity |
| Predicate | terroristRole |
P99240
|
FINISHED |
| Object | aircraft hijacker |
—
|
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: aircraft hijacker | Statement: [Hamza al-Ghamdi, terroristRole, aircraft hijacker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terroristRole Context triple: [Hamza al-Ghamdi, terroristRole, aircraft hijacker]
-
A.
hasTerroristAntagonist
Indicates that the subject work features an antagonist who is a terrorist or engages in terrorism.
-
B.
positionOnTerrorism
Indicates a stance or viewpoint that an entity holds regarding terrorism, such as its causes, legitimacy, or appropriate responses.
-
C.
terroristOrganization
Indicates that an entity is recognized as a group that plans, supports, or carries out acts of terrorism.
-
D.
roleInLibyanCivilWar
Indicates the specific involvement, function, or position an entity had in the context of the Libyan Civil War.
-
E.
roleInManOnFire
Indicates that an entity has a role or participation in the work titled "Man on Fire."
- 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_69d6aadeef688190874bcecd88b3dd9b |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d806c000b88190bfaa646b2dc424b7 |
completed | April 9, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69d7e71436f88190ac7e45a04ea5c987 |
completed | April 9, 2026, 5:51 p.m. |
| PDg | Predicate description generation | batch_69d80010712c819089ea2e31e664abe1 |
completed | April 9, 2026, 7:37 p.m. |
Created at: April 8, 2026, 9:35 p.m.