Triple
T35142747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alice Knight Buffay |
E1014738
|
entity |
| Predicate | surrogatePregnancyArrangedWith |
P107492
|
FINISHED |
| Object | Phoebe Buffay |
—
|
NE NERFINISHED |
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: Phoebe Buffay | Statement: [Alice Knight Buffay, surrogatePregnancyArrangedWith, Phoebe Buffay]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: surrogatePregnancyArrangedWith Context triple: [Alice Knight Buffay, surrogatePregnancyArrangedWith, Phoebe Buffay]
-
A.
usedSurrogacy
Indicates that an individual or couple had a child through the use of a surrogate pregnancy arrangement.
-
B.
hasSurrogatePregnancyFor
chosen
Indicates that one entity is carrying a pregnancy on behalf of another entity, typically with the intention of giving the resulting child to that other entity.
-
C.
adoptionArrangementWith
Indicates a relationship in which one party has a formal or agreed-upon arrangement to adopt another party.
-
D.
plansToHaveChildVia
Indicates an intention or arrangement for one entity to have a child through the involvement or assistance of another entity.
-
E.
providedSpermDonorFor
Indicates that one entity served as the sperm donor used for another entity’s conception or reproductive process.
- 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_69f76dda7c108190a2ffd93eb6c341a7 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78cab90cc8190827145ac515d203b |
completed | May 3, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69f78b9106008190930b3b3675b737d6 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4:02 p.m.