Triple
T24220347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Beaver |
E601433
|
entity |
| Predicate | relationshipToTony Last |
P86783
|
FINISHED |
| Object | Brenda Last's lover |
—
|
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: Brenda Last's lover | Statement: [John Beaver, relationshipToTony Last, Brenda Last's lover]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToTony Last Context triple: [John Beaver, relationshipToTony Last, Brenda Last's lover]
-
A.
relationshipToTony
chosen
Indicates the specific type of relationship or connection that an entity has with Tony.
-
B.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
C.
relationshipToTerry
Indicates the specific type of personal or social relationship that one entity has with Terry.
-
D.
relationshipToTucker
Indicates the specific familial, social, or professional relationship that one entity has to Tucker.
-
E.
relationshipToTracyLord
Indicates the specific type of personal or social relationship an entity has with Tracy Lord.
- 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_69e29537ca548190b94a37ebe1977caf |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f2820cdd3c8190998d6d901224c09f |
completed | April 29, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69f1c448abec8190b87cbf9ed419a309 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:59 p.m.