Triple
T25493322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yusuf ibn Ya‘qub |
E638890
|
entity |
| Predicate | correspondingNameInHebrew |
P125164
|
FINISHED |
| Object | Yosef |
—
|
NE NERFINISHED |
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: Yosef | Statement: [Yusuf ibn Ya‘qub, correspondingNameInHebrew, Yosef]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondingNameInHebrew Context triple: [Yusuf ibn Ya‘qub, correspondingNameInHebrew, Yosef]
-
A.
correspondsToInHebrew
chosen
Indicates that one entity is the Hebrew-language equivalent or counterpart of another entity.
-
B.
hasNameInHebrew
Indicates that an entity is associated with a specific name expressed in the Hebrew language.
-
C.
nameInAramaic
Indicates that an entity has a specific name expressed in the Aramaic language.
-
D.
equivalentGivenNameInEnglish
Indicates that two given names are equivalent in meaning or usage when expressed in English.
-
E.
transliteratedAsInModernIsraeliUsage
Indicates that one entity is the modern Israeli Hebrew transliteration form used to represent the other entity.
- 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_69e75dbbd2a88190b70e1e645de14b9a |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5ffc74fa481909b4fe24a9337f9eb |
completed | May 2, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69f5f7f99dc08190afcfb3bc4dfbec1d |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 21, 2026, 2:39 p.m.