Triple
T34949226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Hanks as adult Josh Baskin |
E1007941
|
entity |
| Predicate | hasMentalAge |
P199201
|
FINISHED |
| Object | 12-year-old boy |
—
|
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: 12-year-old boy | Statement: [Tom Hanks as adult Josh Baskin, hasMentalAge, 12-year-old boy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMentalAge Context triple: [Tom Hanks as adult Josh Baskin, hasMentalAge, 12-year-old boy]
-
A.
hasCognitiveComponent
Indicates that the related entity or process involves or depends on mental activities such as thinking, reasoning, perception, or understanding.
-
B.
hasIQ
Indicates that an entity possesses a specific intelligence quotient (IQ) value or score.
-
C.
hasHighIQ
Indicates that an entity possesses an intelligence level above a specified high threshold.
-
D.
hasAge
Indicates that an entity possesses a specific age value, typically expressed as a number of time units since its birth or creation.
-
E.
canAge
Indicates that one entity has the capability or property of undergoing aging over time.
- F. None of above. chosen
Provenance (4 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_69ff255b84788190a94682f4efe1d0b8 |
completed | May 9, 2026, 12:15 p.m. |
| PD | Predicate disambiguation | batch_69ff24f3ab108190bb017a656cff3d82 |
completed | May 9, 2026, 12:13 p.m. |
| PDg | Predicate description generation | batch_69ff255abca881908ef7635bd2e5af98 |
completed | May 9, 2026, 12:15 p.m. |
Created at: May 3, 2026, 4 p.m.