Triple
T14028322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs David Cameron |
E337520
|
entity |
| Predicate | notCommonlyUsedBy |
P89202
|
FINISHED |
| Object | Samantha Cameron in public |
—
|
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: Samantha Cameron in public | Statement: [Mrs David Cameron, notCommonlyUsedBy, Samantha Cameron in public]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notCommonlyUsedBy Context triple: [Mrs David Cameron, notCommonlyUsedBy, Samantha Cameron in public]
-
A.
notTypicallyUsedFor
Indicates that something is generally not used for a particular purpose, function, or activity under normal circumstances.
-
B.
notUsedAt
Indicates that a particular entity is not utilized, applied, or active at a specified location, time, or context.
-
C.
notAutomaticallyUsedBy
Indicates that something is not used by another entity in an automatic or default manner and instead requires explicit action or configuration to be used.
-
D.
isLessCommonThan
Indicates that one item occurs, appears, or is observed less frequently than another item.
-
E.
usedLessIn
chosen
Indicates that one entity is used with a lower frequency or intensity compared to 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2fa830ac81908cb7df7c9e81e42a |
completed | April 14, 2026, 12:14 p.m. |
| PD | Predicate disambiguation | batch_69de05ab36b48190920efb1869bdb1fe |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:20 p.m.