Triple
T28520139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Jingles |
E721738
|
entity |
| Predicate | befriendedBy |
P150269
|
FINISHED |
| Object | John Coffey |
—
|
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: John Coffey | Statement: [Mr. Jingles, befriendedBy, John Coffey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: befriendedBy Context triple: [Mr. Jingles, befriendedBy, John Coffey]
-
A.
acquaintanceOf
Indicates that one entity knows another in a casual or non-intimate way, without implying close friendship or strong personal ties.
-
B.
eventuallyBefriends
Indicates that one entity, after some passage of time or intervening events, comes to form a friendly or amicable relationship with another entity.
-
C.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
D.
hasSocialTieWith
chosen
Indicates a social relationship or connection exists between two entities, such as friendship, acquaintance, or other interpersonal tie.
-
E.
relationshipToFriends
Indicates the type or nature of the relationship an entity has with its friends.
- 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_69f01a5cbcc4819083fb4e723378713e |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f64fa169e48190b061b3b3014a079d |
completed | May 2, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69f64cb0d8008190912e1430cfaf92aa |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 28, 2026, 3:20 a.m.