Triple
T3252243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Israeli authorities |
E68207
|
entity |
| Predicate | frequentlyMentionedIn |
P5303
|
FINISHED |
| Object | United Nations reports |
—
|
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: United Nations reports | Statement: [Israeli authorities, frequentlyMentionedIn, United Nations reports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequentlyMentionedIn Context triple: [Israeli authorities, frequentlyMentionedIn, United Nations reports]
-
A.
frequentlyDiscussedIn
chosen
Indicates that a topic, subject, or entity is often the focus of conversation, debate, or mention within a particular context or medium.
-
B.
isFrequentlyIncludedIn
Indicates that something is regularly or commonly contained or made part of something else.
-
C.
mentionedAs
Indicates that one entity is referred to or cited by name or description in the context of another entity.
-
D.
frequentlyVisitedBy
Indicates that an entity is regularly or often visited by another entity.
-
E.
mentions
Indicates that one entity refers to, cites, or brings up another entity in some form of communication or content.
- 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_69ad858f74408190bcbd07f967cd7bd0 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaf440bb88190a2450405afae7f1f |
completed | March 8, 2026, 5:17 p.m. |
| PD | Predicate disambiguation | batch_69ada41ae74081909a0d1d696be8e35e |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:09 p.m.