Triple
T34804363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kathleen Kelly |
E1003308
|
entity |
| Predicate | meetsInPersonUnknowingly |
P181498
|
FINISHED |
| Object | Joe Fox |
—
|
NE NERFINISHED |
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: Joe Fox | Statement: [Kathleen Kelly, meetsInPersonUnknowingly, Joe Fox]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meetsInPersonUnknowingly Context triple: [Kathleen Kelly, meetsInPersonUnknowingly, Joe Fox]
-
A.
mayMeet
Indicates that one entity is permitted or has the possibility to meet or come together with another entity.
-
B.
neverSeenOnCamera
Indicates that the subject has not appeared or been captured in any recorded visual media or footage.
-
C.
neverSeenWithout
Indicates that one entity is always accompanied by another and is not observed in situations where the other is absent.
-
D.
acquaintanceOf
Indicates that one entity knows another in a casual or non-intimate way, without implying close friendship or strong personal ties.
-
E.
possiblePresenceIn
Indicates that an entity may be located in, occur in, or exist within a specified place, context, or container, without asserting that it is definitively present there.
- 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_69f76db600b88190989abdf08fce3b27 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ab085088190ace5734dcc9f1167 |
completed | May 3, 2026, 4:41 p.m. |
| PD | Predicate disambiguation | batch_69f7795b1abc8190823664d1caa94649 |
completed | May 3, 2026, 4:35 p.m. |
| PDg | Predicate description generation | batch_69f77a39135081908ae22d2a23b44e74 |
completed | May 3, 2026, 4:39 p.m. |
Created at: May 3, 2026, 3:59 p.m.