Triple
T28954982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eleazar ben Azariah |
E731133
|
entity |
| Predicate | officeTenure |
P161579
|
FINISHED |
| Object | brief tenure as Nasi |
—
|
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: brief tenure as Nasi | Statement: [Eleazar ben Azariah, officeTenure, brief tenure as Nasi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeTenure Context triple: [Eleazar ben Azariah, officeTenure, brief tenure as Nasi]
-
A.
teamTenure
Indicates the duration or length of time an entity has been part of a particular team.
-
B.
denotesTenure
chosen
Indicates that one entity holds or has held a position, role, or office at another entity for a specified period of time.
-
C.
occupationDuration
Indicates the length of time an entity holds or has held a particular occupation or role.
-
D.
tenureType
Indicates the type or category of tenure or contractual engagement that characterizes the relationship between the involved entities.
-
E.
initialTenure
Indicates the starting period or first phase of someone’s tenure in a role, position, or organization.
- 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_69f043eb9bcc819091ac7b07aecb6475 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69fdbaa226708190b8ed96e93aad38de |
completed | May 8, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_69fdb58b07e48190837e00966de050d4 |
completed | May 8, 2026, 10:06 a.m. |
Created at: April 28, 2026, 8:46 a.m.