Triple
T33593118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yvonne Carmichael |
E860482
|
entity |
| Predicate | relationshipTypeWithMarkCostley |
P10690
|
FINISHED |
| Object | clandestine affair |
—
|
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: clandestine affair | Statement: [Yvonne Carmichael, relationshipTypeWithMarkCostley, clandestine affair]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithMarkCostley Context triple: [Yvonne Carmichael, relationshipTypeWithMarkCostley, clandestine affair]
-
A.
relationshipTypeWithCeliaCoplestone
Indicates the specific nature or category of relationship that an entity has with Celia Coplestone.
-
B.
relationshipTypeWith Mona Stangley
Indicates the specific type or nature of relationship that an entity has with Mona Stangley.
-
C.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
D.
relationshipTypeWithMarkMcPherson
Indicates the specific nature or category of relationship that an entity has with Mark McPherson.
-
E.
relationshipTypeWithHesterCollyer
Indicates the specific nature or category of relationship that an entity has with Hester Collyer.
- 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_69f3497e70e48190951c94d072879bec |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:40 a.m.