Triple
T15441059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard Nixon in Frost/Nixon |
E369898
|
entity |
| Predicate | ageDepicted |
P13483
|
FINISHED |
| Object | elderly |
—
|
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: elderly | Statement: [Richard Nixon in Frost/Nixon, ageDepicted, elderly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageDepicted Context triple: [Richard Nixon in Frost/Nixon, ageDepicted, elderly]
-
A.
ageDepictionConsistency
Indicates that the depicted age of an entity is consistent with its known or expected age within the given context.
-
B.
portraysFromAge
Indicates that one entity depicts another entity starting from a specified age of the depicted entity.
-
C.
portraysAgeGroup
chosen
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
-
D.
sitterAgeAtTimeOfPortrait
Indicates the age of the sitter at the specific time when the portrait was created or captured.
-
E.
ageDuringNarration
Indicates that an entity has a specified age at the time when the described narrative or event is taking place.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03eddf258819082679970b7d2b6af |
completed | April 16, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69ded28276f481908c2038bb301e57cf |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:21 a.m.