Triple
T21212335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian Young Lawyers Association v. State of Kerala |
E522750
|
entity |
| Predicate | ageGroupConcerned |
P2736
|
FINISHED |
| Object | women between the ages of 10 and 50 |
—
|
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: women between the ages of 10 and 50 | Statement: [Indian Young Lawyers Association v. State of Kerala, ageGroupConcerned, women between the ages of 10 and 50]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageGroupConcerned Context triple: [Indian Young Lawyers Association v. State of Kerala, ageGroupConcerned, women between the ages of 10 and 50]
-
A.
ageGroupInvolved
Indicates that a particular age group participates in, is affected by, or is otherwise involved in the specified event or relationship.
-
B.
ageGroup
Indicates the categorical age range or bracket to which an entity belongs.
-
C.
ageGroupIndicated
Indicates that a specific age range or category is identified or assigned to an entity.
-
D.
ageRange
chosen
Indicates the span of ages within which an entity or relationship is considered valid or applicable.
-
E.
ageGroupRole
Indicates the role or function an entity has within a specific age group classification.
- 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_69e0b511ed84819099b449b4a111085c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7346f762c8190a9f57d9e00d94d28 |
completed | April 21, 2026, 8:25 a.m. |
| PD | Predicate disambiguation | batch_69e5f6094e3c81909ee9699e00d371f7 |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:38 p.m.