Triple
T13219838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jason Compson II |
E314719
|
entity |
| Predicate | relationshipToDilseyGibson |
P108583
|
FINISHED |
| Object | employer |
—
|
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 | Statement: [Jason Compson II, relationshipToDilseyGibson, employer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToDilseyGibson Context triple: [Jason Compson II, relationshipToDilseyGibson, employer]
-
A.
relationshipToDeloris
Indicates the specific type of personal, familial, or social relationship that one entity has with the entity named Deloris.
-
B.
relationshipToElaineRisley
Indicates the nature or type of connection an entity has to Elaine Risley, such as familial, social, or professional relationship.
-
C.
relationshipToDudley
Indicates the specific familial or social relationship that one entity has to the person named Dudley.
-
D.
relationshipToDianaGoodman
Indicates a specified type of relationship or connection that an entity has to Diana Goodman.
-
E.
relationshipToHollyGolightly
Indicates the nature or type of relationship an entity has with Holly Golightly.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf581508190883033f0c961736a |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc938f081909f123bdf1263ff7f |
completed | April 10, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69d98c959ba08190adf29dc0c4e1fca6 |
completed | April 10, 2026, 11:49 p.m. |
Created at: April 9, 2026, 9:18 p.m.