Triple
T9110696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Brougham (The Bishop's Wife) |
E218592
|
entity |
| Predicate | focusOf |
P86548
|
FINISHED |
| Object | angelic intervention |
—
|
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: angelic intervention | Statement: [Henry Brougham (The Bishop's Wife), focusOf, angelic intervention]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusOf Context triple: [Henry Brougham (The Bishop's Wife), focusOf, angelic intervention]
-
A.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
B.
focusType
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
-
C.
focusesBy
Indicates that one entity directs its attention, effort, or emphasis toward another entity or specific aspect of it.
-
D.
focusPosition
Indicates the spatial or logical position at which attention, concentration, or processing is currently directed within a given context.
-
E.
focusModel
Indicates that one entity serves as the primary or central model that another entity is directed toward, based on, or concentrated on.
- 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_69ca83dc94ac8190b9ef42684d36ff39 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca847102881908f9d86ce9883fb1a |
completed | April 1, 2026, 5:08 a.m. |
| PD | Predicate disambiguation | batch_69cc65fe5be081909d4470d6317b14a6 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc66d7bf648190b8bff5b584b84975 |
completed | April 1, 2026, 12:29 a.m. |
Created at: March 30, 2026, 7:16 p.m.