Triple
T1075063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matt Eberflus |
E23816
|
entity |
| Predicate | hasExperienceIn |
P17879
|
FINISHED |
| Object | NFL coaching |
—
|
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 coaching | Statement: [Matt Eberflus, hasExperienceIn, NFL coaching]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExperienceIn Context triple: [Matt Eberflus, hasExperienceIn, NFL coaching]
-
A.
typeOfExperience
Indicates that one entity specifies the category or nature of an experience associated with another entity.
-
B.
hasWorkedIn
chosen
Indicates that a person has been employed or has performed work within a particular organization, location, or domain for some period of time.
-
C.
experienceType
Indicates the specific kind or category of experience associated with an entity or event.
-
D.
hasWorkedFor
Indicates that an entity has been employed by or has provided work or services to another entity.
-
E.
primaryExperience
Indicates that one entity is the main or most significant experience associated with another entity, as opposed to secondary or supporting experiences.
- 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b92e480c81909a848b48c196a293 |
completed | March 1, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69a4b73ba8208190be7f3cef8c18689b |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.