Triple
T31040624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mahmud Abouhalima |
E790979
|
entity |
| Predicate | terroristAttackLocation |
P171124
|
FINISHED |
| Object | New York City |
—
|
NE NERFINISHED |
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: New York City | Statement: [Mahmud Abouhalima, terroristAttackLocation, New York City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terroristAttackLocation Context triple: [Mahmud Abouhalima, terroristAttackLocation, New York City]
-
A.
terroristAttackTargetCountry
Indicates that a terrorist attack is directed against or occurs within the specified country as its target.
-
B.
bombingLocation
Indicates the place where a bombing event occurs or is carried out.
-
C.
assassinationAttemptLocation
Indicates the place where an attempted assassination occurred or was intended to occur.
-
D.
locationOfAttacksCondemned
Indicates that a specific location is the site of attacks that have been explicitly denounced or condemned.
-
E.
deadliestTerroristAttackIn
Indicates that a terrorist attack is the most lethal one that has occurred within a specified place or region.
- 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_69f224ca2fa881908a3ac5fedf207b90 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f698ad83a08190a6834056ccc3e3a4 |
completed | May 3, 2026, 12:37 a.m. |
| PD | Predicate disambiguation | batch_69f69664142c8190bc695501056b0236 |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f697e92e2c8190bed50d5ba0981b64 |
completed | May 3, 2026, 12:33 a.m. |
Created at: April 29, 2026, 8:59 p.m.