Triple
T6851799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frederick Altamont Cornwallis Twistleton |
E158034
|
entity |
| Predicate | hasAgeDescriptor |
P45004
|
FINISHED |
| Object | elderly |
—
|
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: elderly | Statement: [Frederick Altamont Cornwallis Twistleton, hasAgeDescriptor, elderly]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgeDescriptor Context triple: [Frederick Altamont Cornwallis Twistleton, hasAgeDescriptor, elderly]
-
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.
hasRelativeAge
Indicates that one entity has an age that is defined or compared in relation to the age of another entity.
-
D.
hasAgeFocus
Indicates a relationship where something is characterized or distinguished by a particular age group or age-related emphasis.
-
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_69c6882fae988190864cbba788c5ebb4 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d84e6fb08190915954be5b0df2d8 |
completed | March 27, 2026, 7:19 p.m. |
| PD | Predicate disambiguation | batch_69c6d0a12834819097d7e6c0b823745e |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:20 p.m.