Triple
T29316329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Operation Amud Anan |
E743389
|
entity |
| Predicate | IronDomeEffect |
P27065
|
FINISHED |
| Object | intercepted many incoming rockets |
—
|
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: intercepted many incoming rockets | Statement: [Operation Amud Anan, IronDomeEffect, intercepted many incoming rockets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: IronDomeEffect Context triple: [Operation Amud Anan, IronDomeEffect, intercepted many incoming rockets]
-
A.
airDefenseSystem
Indicates a defensive military system designed to detect, track, and engage airborne threats such as aircraft or missiles.
-
B.
airDefenseSystemInvolved
chosen
Indicates that an air defense system participates in or is used during a specific event, operation, or engagement.
-
C.
airDefenseSystemComponent
Indicates that one entity is a component or subsystem of an air defense system associated with another entity.
-
D.
airDefenseArmament
Indicates the weapons or systems specifically equipped on an entity for defending against aerial threats such as aircraft or missiles.
-
E.
defensiveCapability
Indicates the ability or capacity of an entity to protect itself or others against threats, attacks, or harm.
- 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_69f0912502c8819087d9e8398ee991a8 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f665ec3ee481909ae35e76899a7056 |
completed | May 2, 2026, 9 p.m. |
| PD | Predicate disambiguation | batch_69f660f2e3708190ab658652bcfc04d0 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 1:20 p.m.