Triple
T20391438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T-850 |
E498093
|
entity |
| Predicate | appearanceActorAge |
P94896
|
FINISHED |
| Object | middle-aged Arnold Schwarzenegger |
—
|
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: middle-aged Arnold Schwarzenegger | Statement: [T-850, appearanceActorAge, middle-aged Arnold Schwarzenegger]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearanceActorAge Context triple: [T-850, appearanceActorAge, middle-aged Arnold Schwarzenegger]
-
A.
portrayedByCharacterAgeApprox
Indicates that an entity is portrayed by a character whose age is approximately a specified value or age range.
-
B.
characterAgeDescriptor
chosen
Indicates how a character’s age is qualitatively described or categorized (e.g., young, middle-aged, elderly) rather than given as a specific number.
-
C.
portraysFromAge
Indicates that one entity depicts another entity starting from a specified age of the depicted entity.
-
D.
ageOfActorAtTime
Indicates the age that an actor has at a specified point in time.
-
E.
portraysAgeGroup
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
- 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_69e0b4a71ebc8190b153a36c738730f4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6790f8d9c819093038f6bb6f47a92 |
completed | April 20, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69e57648be3c81908256838228cabf5c |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:28 a.m.