Triple
T15992674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taissa Turner |
E387872
|
entity |
| Predicate | ageGroupInPresentTimeline |
P19123
|
FINISHED |
| Object | adult |
—
|
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: adult | Statement: [Taissa Turner, ageGroupInPresentTimeline, adult]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageGroupInPresentTimeline Context triple: [Taissa Turner, ageGroupInPresentTimeline, adult]
-
A.
ageGroup
chosen
Indicates the categorical age range or bracket to which an entity belongs.
-
B.
ageRange
Indicates the span of ages within which an entity or relationship is considered valid or applicable.
-
C.
ageGroupStructure
Indicates how a population or set of entities is distributed across different age groups or age categories.
-
D.
ageGroupInvolved
Indicates that a particular age group participates in, is affected by, or is otherwise involved in the specified event or relationship.
-
E.
inUniverseAgeGroup
Indicates that an entity belongs to a specified age group within a particular fictional or defined universe or setting.
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4e871c819082d7b1c1eaf5b4fe |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d9d8e881909b559a3e3ca21d24 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:54 a.m.