Triple
T4532574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dublin and Monaghan bombings |
E106331
|
entity |
| Predicate | numberOfAttacks |
P57304
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Dublin and Monaghan bombings, numberOfAttacks, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfAttacks Context triple: [Dublin and Monaghan bombings, numberOfAttacks, 4]
-
A.
attackerStrength
Indicates the level or magnitude of power, force, or capability possessed by the attacking entity in a given interaction or scenario.
-
B.
numberOfInvaders
Indicates the quantity of entities classified as invaders associated with a given subject or context.
-
C.
attackedIn
Indicates that one entity carried out an attack in the location, context, or time frame specified by another entity or value.
-
D.
objectiveOfAttackers
Indicates the target or goal that attackers aim to reach or affect through their attack.
-
E.
notableAttack
Indicates that an entity carried out, was involved in, or is strongly associated with a particularly significant or well-known attack.
- 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_69bd43f3d6e08190a91824f833d51bbe |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd579f27ac8190ae9a4252109e56e1 |
completed | March 20, 2026, 2:20 p.m. |
| PD | Predicate disambiguation | batch_69bd521edd00819099dfccaa65dddd61 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56b3e4c88190a7ade3d0ed0ab606 |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:03 p.m.