Triple
T14634579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alonzo "Fonny" Hunt |
E343569
|
entity |
| Predicate | relationshipTypeWithTish Rivers |
P10690
|
FINISHED |
| Object | fiancé |
—
|
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: fiancé | Statement: [Alonzo "Fonny" Hunt, relationshipTypeWithTish Rivers, fiancé]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithTish Rivers Context triple: [Alonzo "Fonny" Hunt, relationshipTypeWithTish Rivers, fiancé]
-
A.
riverRelation
Indicates a spatial or geographic relationship between one river and another, such as confluence, branching, or relative positioning.
-
B.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
C.
closelyAssociatedRiver
Indicates a river that is geographically or functionally closely connected to the subject, such as flowing nearby, through, or otherwise strongly linked to it.
-
D.
betweenRiver
Indicates a spatial relationship where something is located in the area separating two rivers or lies in the intermediate region defined by them.
-
E.
mentionsRiver
Indicates that an entity refers to or brings up a river in some form of content or communication.
- 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4ab9578819085b4cf7244d30d87 |
completed | April 14, 2026, 9:42 p.m. |
| PD | Predicate disambiguation | batch_69de657359c88190b082e3e9f86fc1d7 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:26 a.m.