Triple
T24220326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brenda Last |
E601432
|
entity |
| Predicate | relationshipToTonyLast |
P86783
|
FINISHED |
| Object | wife |
—
|
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: wife | Statement: [Brenda Last, relationshipToTonyLast, wife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToTonyLast Context triple: [Brenda Last, relationshipToTonyLast, wife]
-
A.
relationshipToTony
chosen
Indicates the specific type of relationship or connection that an entity has with Tony.
-
B.
relationshipToTerry
Indicates the specific type of personal or social relationship that one entity has with Terry.
-
C.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
D.
relationshipToTucker
Indicates the specific familial, social, or professional relationship that one entity has to Tucker.
-
E.
relationshipToMike
Indicates the specific type of personal, social, or familial relationship that an entity has with Mike.
- 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.