Triple
T277195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brendan Rodgers |
E5274
|
entity |
| Predicate | childOccupation |
P8458
|
FINISHED |
| Object | Anton Rodgers is a professional footballer |
—
|
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: Anton Rodgers is a professional footballer | Statement: [Brendan Rodgers, childOccupation, Anton Rodgers is a professional footballer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: childOccupation Context triple: [Brendan Rodgers, childOccupation, Anton Rodgers is a professional footballer]
-
A.
children
Indicates that one entity is the offspring or direct descendant of another entity.
-
B.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
C.
parentOccupation
Indicates that one entity has an occupation which is the job or profession of the other entity’s parent.
-
D.
motherOccupation
Indicates the type of job or profession that a person's mother has.
-
E.
fatherOccupation
Indicates the type of job or profession held by a person's father.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25ded68c88190b1fc595ce329aeb9 |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b7480e881909399beccfc7ffb81 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25c2d94388190aeda17ddd42b4ac9 |
completed | Feb. 28, 2026, 3:08 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.