Triple
T12596644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American South Conference |
E300748
|
entity |
| Predicate | hadAutomaticQualifierStatus |
P105598
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [American South Conference, hadAutomaticQualifierStatus, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadAutomaticQualifierStatus Context triple: [American South Conference, hadAutomaticQualifierStatus, yes]
-
A.
hadSpecialStatusIn
Indicates that an entity possessed a particular special, exceptional, or non-standard status within a specified context or time period.
-
B.
hasQualification
Indicates that an entity possesses a specific qualification, credential, or competency.
-
C.
automaticQualifiers
Indicates that certain attributes or conditions are assigned or inferred automatically as qualifiers for the relationship or action, without requiring explicit specification.
-
D.
hasQualifier
Indicates that one entity serves as a qualifier or modifier that further specifies or restricts the meaning or scope of another entity or statement.
-
E.
hasHad
Indicates that an entity previously experienced, possessed, or was involved in something at some point in the past.
- 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954e6e20481908bca684c4b497c48 |
completed | April 10, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69d95416cbd88190b2c65196162349bc |
completed | April 10, 2026, 7:48 p.m. |
| PDg | Predicate description generation | batch_69d954e351f88190869220d46e0ce282 |
completed | April 10, 2026, 7:52 p.m. |
Created at: April 9, 2026, 5:08 p.m.