Triple
T28118634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rory McKenna |
E710711
|
entity |
| Predicate | drawsAttentionOf |
P86548
|
FINISHED |
| Object | human government agents |
—
|
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: human government agents | Statement: [Rory McKenna, drawsAttentionOf, human government agents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drawsAttentionOf Context triple: [Rory McKenna, drawsAttentionOf, human government agents]
-
A.
attracts
Indicates that one entity exerts a force or influence that draws another entity toward it.
-
B.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
C.
focusTrait
Indicates that one entity is characterized by, or primarily associated with, a particular trait or attribute of another entity.
-
D.
focusOf
chosen
Indicates that one entity is the primary subject, target, or center of attention, activity, or interest for another entity.
-
E.
hasAttentionPattern
Indicates that one entity exhibits a specific, identifiable pattern of attention or focus directed toward another entity or stimulus.
- 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_69ef9b72f63081909dfbc2c1ddae86c6 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f640f6569081909b9aff26d85bc8c2 |
completed | May 2, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69f63c6a8474819091b8c6fe98e3862d |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 9:15 p.m.