Triple
T754850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivy League women’s basketball |
E15530
|
entity |
| Predicate | ageGroup |
P19123
|
FINISHED |
| Object | university students |
—
|
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: university students | Statement: [Ivy League women’s basketball, ageGroup, university students]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageGroup Context triple: [Ivy League women’s basketball, ageGroup, university students]
-
A.
ageRange
Indicates the span of ages within which an entity or relationship is considered valid or applicable.
-
B.
portraysAgeGroup
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
-
C.
lifeStage
Indicates the specific phase or period in an entity’s development or lifecycle that it is currently in.
-
D.
ageProgression
Indicates a temporal relationship where an entity’s age increases or advances over time.
-
E.
hasAge
Indicates that an entity possesses a specific age value, typically expressed as a number of time units since its birth or creation.
- F. None of above. chosen
Provenance (4 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a66820548190b373deb117187c2c |
completed | March 1, 2026, 8:49 p.m. |
| PD | Predicate disambiguation | batch_69a4a501c4cc81908de6d63e3d4f60d7 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a5bed20c81909ecc28bf42594e72 |
completed | March 1, 2026, 8:46 p.m. |
Created at: March 1, 2026, 7:37 p.m.