Triple
T11091480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daisy Fuller |
E262264
|
entity |
| Predicate | ageProgressionDescription |
P92996
|
FINISHED |
| Object | ages normally while Benjamin Button ages in reverse |
—
|
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: ages normally while Benjamin Button ages in reverse | Statement: [Daisy Fuller, ageProgressionDescription, ages normally while Benjamin Button ages in reverse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageProgressionDescription Context triple: [Daisy Fuller, ageProgressionDescription, ages normally while Benjamin Button ages in reverse]
-
A.
ageProgression
Indicates a temporal relationship where an entity’s age increases or advances over time.
-
B.
ageProgressionDirection
chosen
Indicates the direction in which an entity’s age changes over time within a given process or representation (e.g., from younger to older or older to younger).
-
C.
ageDetail
Indicates a detailed specification of an entity’s age, such as exact value, range, or related age attributes.
-
D.
lifeProgression
Indicates the sequence or advancement of an entity through different stages or phases of its life or development.
-
E.
ageStatus
Indicates the relationship between an entity and its classification into an age-related category or status (e.g., minor, adult, senior).
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799ebae8c8190987b474adb7ede47 |
completed | April 9, 2026, 12:22 p.m. |
| PD | Predicate disambiguation | batch_69d744185a5881909ba4cf151d1798ec |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:27 p.m.