Triple
T13467006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jason Compson III |
E311528
|
entity |
| Predicate | relationshipToCarolineCompson |
P110484
|
FINISHED |
| Object | husband |
—
|
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: husband | Statement: [Jason Compson III, relationshipToCarolineCompson, husband]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToCarolineCompson Context triple: [Jason Compson III, relationshipToCarolineCompson, husband]
-
A.
relationshipToMissWatson
Indicates the type or nature of a person's relational connection to Miss Watson (e.g., familial, social, or other defined relationship).
-
B.
relationshipToBlancheDuBois
Indicates the specific familial, social, or interpersonal connection an entity has with Blanche DuBois.
-
C.
relationshipToCatherine
Indicates the specific familial, social, or interpersonal connection that one entity has to the person named Catherine.
-
D.
relationshipToHenry
Indicates the specific type of relationship or connection that an entity has to Henry.
-
E.
relationshipToJoeBuck
Indicates the specific familial, social, or professional relationship that one entity has to the person Joe Buck.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf101a1081909f2aba6da47baacc |
completed | April 12, 2026, 2:41 p.m. |
| PD | Predicate disambiguation | batch_69dbadfddefc81909ef7fde23b181b5c |
completed | April 12, 2026, 2:36 p.m. |
| PDg | Predicate description generation | batch_69dbaecc98cc8190829f5be759c4f1e3 |
completed | April 12, 2026, 2:40 p.m. |
Created at: April 9, 2026, 9:42 p.m.