Triple
T4066937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of Tajikistan |
E86345
|
entity |
| Predicate | eligibleAgeRequirement |
P42793
|
FINISHED |
| Object | at least 35 years old |
—
|
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: at least 35 years old | Statement: [President of Tajikistan, eligibleAgeRequirement, at least 35 years old]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eligibleAgeRequirement Context triple: [President of Tajikistan, eligibleAgeRequirement, at least 35 years old]
-
A.
maximumAgeRequirement
Indicates that there is an upper age limit that an entity must not exceed in order for a condition, participation, or eligibility to apply.
-
B.
typicalEligibilityAge
Indicates the usual or standard age at which an entity qualifies for or becomes eligible for a particular status, benefit, or activity.
-
C.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
D.
setsMinimumAge
chosen
Indicates that an entity establishes the lowest permissible age required for participation, access, or eligibility in relation to another entity or activity.
-
E.
ageStatus
Indicates the relationship between an entity and its classification into an age-related category or status (e.g., minor, adult, senior).
- 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_69aed93c69208190a4efac0efe3cd69b |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefbf73a1c81909f1741f4ecf55f98 |
completed | March 9, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69aef9061d2481908307cafc9e9b32c0 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:38 p.m.