Triple
T34949225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Hanks as adult Josh Baskin |
E1007941
|
entity |
| Predicate | hasAgeState |
P45004
|
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: [Tom Hanks as adult Josh Baskin, hasAgeState, adult]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgeState Context triple: [Tom Hanks as adult Josh Baskin, hasAgeState, adult]
-
A.
hasAge
Indicates that an entity possesses a specific age value, typically expressed as a number of time units since its birth or creation.
-
B.
ageStatus
chosen
Indicates the relationship between an entity and its classification into an age-related category or status (e.g., minor, adult, senior).
-
C.
canAge
Indicates that one entity has the capability or property of undergoing aging over time.
-
D.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
E.
canAgeFor
Indicates that one entity is capable of undergoing an aging or maturation process for the benefit, use, or context of another entity.
- 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_69f76dc5d4308190b77553ee07b1ede6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782ccb1ec8190a15e00c9e678e5da |
completed | May 3, 2026, 5:15 p.m. |
| PD | Predicate disambiguation | batch_69f781020cc4819088c40cb8589504e4 |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.