Triple
T27099190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marlon Dingle |
E686390
|
entity |
| Predicate | hasCousinInFamily |
P1999
|
FINISHED |
| Object | Charity Dingle |
—
|
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: Charity Dingle | Statement: [Marlon Dingle, hasCousinInFamily, Charity Dingle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCousinInFamily Context triple: [Marlon Dingle, hasCousinInFamily, Charity Dingle]
-
A.
hasFamilialTieTo
Indicates a relationship where two entities are connected by family bonds, such as by blood, marriage, or adoption.
-
B.
hasSiblingInRealLife
Indicates that one person has another person as their sibling in real life, outside of any fictional or virtual context.
-
C.
hasUncleOfFriend
Indicates that one person is the uncle of another person’s friend.
-
D.
cousin
chosen
Indicates a familial relationship where two people share at least one grandparent but are not siblings.
-
E.
siblingOrRelative
Indicates that two entities are related to each other by blood, marriage, or family ties, including but not limited to being siblings.
- 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_69ef1489f8b481908e24a1985982bd26 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69feba0f09508190b3e871c62b19ec7f |
completed | May 9, 2026, 4:37 a.m. |
| PD | Predicate disambiguation | batch_69feb957fe7c8190969fb31a6d1a59c8 |
completed | May 9, 2026, 4:34 a.m. |
Created at: April 27, 2026, 8:46 a.m.