Triple
T13676043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moira O’Hara |
E327879
|
entity |
| Predicate | hasAgeAppearance |
P45004
|
FINISHED |
| Object | young adult (to men) |
—
|
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: young adult (to men) | Statement: [Moira O’Hara, hasAgeAppearance, young adult (to men)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgeAppearance Context triple: [Moira O’Hara, hasAgeAppearance, young adult (to men)]
-
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.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
C.
hasAgeFocus
Indicates a relationship where something is characterized or distinguished by a particular age group or age-related emphasis.
-
D.
hasCharacterAppearance
Indicates that a character appears or is visually represented within a given work, scene, or context.
-
E.
ageStatus
chosen
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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc65c04988190b675e6fb7241e53c |
completed | April 12, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8d8d0881908d6e89954f44eed4 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:53 p.m.