Triple
T35848937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | בוזי |
E1036292
|
entity |
| Predicate | rarityOfName |
P7075
|
FINISHED |
| Object | שם מקראי נדיר |
—
|
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: שם מקראי נדיר | Statement: [בוזי, rarityOfName, שם מקראי נדיר]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rarityOfName Context triple: [בוזי, rarityOfName, שם מקראי נדיר]
-
A.
isRelativelyRareName
Indicates that the referenced name occurs infrequently relative to other names in the relevant population or dataset.
-
B.
hasGivenNameFrequency
Indicates the frequency or commonness with which a particular given name occurs within a specified population or context.
-
C.
rarity
chosen
Indicates how uncommon or infrequently an entity or event occurs relative to others in a given context.
-
D.
namePopularityType
Indicates the category or type of popularity associated with a given name (e.g., how or in what way the name is considered popular).
-
E.
namePopularityRegion
Indicates the geographic region or area in which a particular name has a certain level of popularity or usage.
- 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_69f76e1a29e8819088280f26096aeb55 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aa3883d48190b05e3d2da7a017ae |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d435288190b30b1991fb003121 |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:06 p.m.