Triple
T3525581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beit Hanoun |
E74530
|
entity |
| Predicate | frequentlyAffectedBy |
P25489
|
FINISHED |
| Object | military operations |
—
|
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: military operations | Statement: [Beit Hanoun, frequentlyAffectedBy, military operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequentlyAffectedBy Context triple: [Beit Hanoun, frequentlyAffectedBy, military operations]
-
A.
areAffectedBy
chosen
Indicates that one entity experiences an effect, influence, or impact as a result of another entity or event.
-
B.
frontAffected
Indicates that an action, event, or condition primarily impacts the front side or front-facing part of an entity.
-
C.
affectedPerson
Indicates that a particular person is impacted or influenced by an event, action, or condition.
-
D.
affectedArea
Indicates the specific region or extent over which an event, condition, or influence has an impact.
-
E.
isFrequently
Indicates that an action, state, or relationship occurs often or with high regularity between the related entities.
- 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_69ad85d0c5488190a3d8e02ebd01a1aa |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc6a8d0c819094d38b9c47fb67b4 |
completed | March 8, 2026, 6:14 p.m. |
| PD | Predicate disambiguation | batch_69adae121a048190b03825a001d21f49 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:19 p.m.