Triple
T26829080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerald Arbuthnot |
E675446
|
entity |
| Predicate | decisionPoint |
P82953
|
FINISHED |
| Object | must choose between career and loyalty to his mother |
—
|
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: must choose between career and loyalty to his mother | Statement: [Gerald Arbuthnot, decisionPoint, must choose between career and loyalty to his mother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: decisionPoint Context triple: [Gerald Arbuthnot, decisionPoint, must choose between career and loyalty to his mother]
-
A.
decisionPointFor
chosen
Indicates a point in a process or workflow at which a choice must be made that determines which subsequent path or outcome will follow.
-
B.
decisionSplit
Indicates that a single decision point branches into multiple alternative outcomes or paths.
-
C.
decisionType
Indicates the specific category or nature of a decision associated with an entity or event.
-
D.
decisionDirection
Indicates the orientation or course (e.g., choice, stance, or path) that a decision takes relative to available options or influencing factors.
-
E.
decisionOutput
Indicates that a decision-making process produces or yields a particular outcome or result.
- 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_69eee9b776448190993a60b67fcc9545 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f62d53ad58819080c5227c7a729d15 |
completed | May 2, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69f62c15952881908a5ea0c25904afec |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 5 a.m.