Triple
T37109690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julian Marty |
E918949
|
entity |
| Predicate | relationshipWithRay |
P175131
|
FINISHED |
| Object | employer-employee |
—
|
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: employer-employee | Statement: [Julian Marty, relationshipWithRay, employer-employee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipWithRay Context triple: [Julian Marty, relationshipWithRay, employer-employee]
-
A.
relationshipToRa
Indicates a specified type of relational connection that an entity has to the entity Ra.
-
B.
relationshipWithRayBarone
Indicates that an entity has some form of personal relationship or connection with Ray Barone.
-
C.
relationshipToRyanBingham
Indicates the specific type of personal or social relationship an entity has with Ryan Bingham.
-
D.
haveRelationshipWith
chosen
Indicates that one entity is in some form of defined relationship or association with another entity.
-
E.
relationshipToAlice
Indicates the specific type of relationship or connection that an entity has with Alice.
- 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_69f76e9b99c8819096164b21ff5bd996 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:14 p.m.