Triple
T12381978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abedi Pele |
E295765
|
entity |
| Predicate | childrenProfession |
P8458
|
FINISHED |
| Object | professional footballers |
—
|
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: professional footballers | Statement: [Abedi Pele, childrenProfession, professional footballers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: childrenProfession Context triple: [Abedi Pele, childrenProfession, professional footballers]
-
A.
childOccupation
chosen
Indicates that a person’s child holds or performs a particular occupation or job.
-
B.
children
Indicates that one entity is the offspring or direct descendant of another entity.
-
C.
familyProfession
Indicates that a person’s profession is shared with or traditionally practiced within their family, reflecting an occupational lineage or family trade.
-
D.
memberProfession
Indicates that a member or individual holds or practices a particular profession or occupation.
-
E.
includesProfession
Indicates that one entity’s set of attributes, roles, or members contains a specific profession as part of it.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fbb3a2481908c2fcb5e6488eb3c |
completed | April 10, 2026, 6:21 p.m. |
| PD | Predicate disambiguation | batch_69d93ed256788190b704cad171a4824e |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.