Triple
T1211703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AT&T Byron Nelson |
E26013
|
entity |
| Predicate | tourLevel |
P25029
|
FINISHED |
| Object | professional |
—
|
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 | Statement: [AT&T Byron Nelson, tourLevel, professional]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourLevel Context triple: [AT&T Byron Nelson, tourLevel, professional]
-
A.
teamLevel
Indicates the hierarchical rank or tier at which a team operates within an organization, competition, or structure.
-
B.
trainingLevel
Indicates the degree or stage of training or skill development that an entity has attained.
-
C.
touringActivity
Indicates an activity where an entity travels from place to place, typically for visiting, performing, or sightseeing purposes.
-
D.
sponsorLevel
Indicates the degree or tier of sponsorship that one entity provides to another.
-
E.
competitionLevel
Indicates the degree or intensity of competitive pressure or rivalry present in a given context or interaction.
- 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_69a4948331fc8190b531ac9bec71c491 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bde581308190bbe30683bf6c48c3 |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb62a7c08190a79dcb6ff72ac99b |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bc6d5b7881908091e40c8695ef53 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:46 p.m.