Triple
T2997916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joan Bennett Kennedy |
E81114
|
entity |
| Predicate | causeOfPublicAttention |
P694
|
FINISHED |
| Object | marriage to Ted Kennedy |
—
|
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: marriage to Ted Kennedy | Statement: [Joan Bennett Kennedy, causeOfPublicAttention, marriage to Ted Kennedy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfPublicAttention Context triple: [Joan Bennett Kennedy, causeOfPublicAttention, marriage to Ted Kennedy]
-
A.
causeOfReputation
Indicates that one entity is the reason or source for another entity’s reputation.
-
B.
causeOf
chosen
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
C.
hasBeenSubjectOf
Indicates that an entity has previously been the focus or target of a particular action, process, or investigation.
-
D.
subjectNotableFor
Indicates that the subject is especially recognized or distinguished for a particular attribute, achievement, role, or characteristic.
-
E.
notableExposure
Indicates that an entity has received significant public attention, visibility, or coverage, making it notably exposed or recognized.
- 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_69ad8b187fc8819085914d3c9ea3142d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99f612148190a5a565ba2ecc4fc0 |
completed | March 8, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69ad9615fefc8190ad96da92519cb7a3 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:59 p.m.