Triple
T25137942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dean of NFL Referees |
E629712
|
entity |
| Predicate | refersToPersonType |
P4342
|
FINISHED |
| Object | NFL referee |
—
|
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: NFL referee | Statement: [Dean of NFL Referees, refersToPersonType, NFL referee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refersToPersonType Context triple: [Dean of NFL Referees, refersToPersonType, NFL referee]
-
A.
refersToPerson
Indicates that one entity is making reference to, mentioning, or pointing specifically to a particular person.
-
B.
appliesToPersonType
Indicates that something (such as a rule, condition, or attribute) is relevant or applicable specifically to a certain type or category of person.
-
C.
refersToPersonFrom
Indicates that one entity makes reference to, mentions, or is about a person originating from or associated with a particular place or group.
-
D.
refersToRole
chosen
Indicates that one entity designates, mentions, or points to another entity specifically in its capacity as a role or position.
-
E.
appliesToPerson
Indicates that something (such as a rule, condition, or attribute) is relevant or applicable to a specific person.
- 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_69e2ff338250819096ff6c8892804389 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f606c79ad081908369605f72e65ca6 |
completed | May 2, 2026, 2:14 p.m. |
| PD | Predicate disambiguation | batch_69f602ce79ec8190b8336c2b9de18ac7 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 18, 2026, 6:29 a.m.