Triple
T9437864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Idabel Thompkins |
E227560
|
entity |
| Predicate | hasRelationshipTypeWithJoelKnox |
P88899
|
FINISHED |
| Object | friendship |
—
|
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: friendship | Statement: [Idabel Thompkins, hasRelationshipTypeWithJoelKnox, friendship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipTypeWithJoelKnox Context triple: [Idabel Thompkins, hasRelationshipTypeWithJoelKnox, friendship]
-
A.
hasRelationshipTypeWithCollinFenwick
Indicates that an entity has a specific type of relationship or connection with Collin Fenwick.
-
B.
relationshipTypeWith Alicia Johns
Indicates the specific type or nature of the relationship that an entity has with Alicia Johns.
-
C.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
D.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
E.
relationshipToJosephCooper
Indicates the specific familial, social, or professional relationship that one entity has to Joseph Cooper.
- 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_69ca8437a7ac81908651de48f2d2141d |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd7edff5e881909b72976e8909ba4b |
completed | April 1, 2026, 8:24 p.m. |
| PD | Predicate disambiguation | batch_69cca55548488190b171ae695a3212de |
completed | April 1, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69cca89b3368819087a3d69270c1f185 |
completed | April 1, 2026, 5:09 a.m. |
Created at: March 30, 2026, 7:50 p.m.