Triple
T31609903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martha Strabel Van Cleve |
E806596
|
entity |
| Predicate | spouseIn |
P193723
|
FINISHED |
| Object | Heaven Can Wait (1943 film) |
—
|
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: Heaven Can Wait (1943 film) | Statement: [Martha Strabel Van Cleve, spouseIn, Heaven Can Wait (1943 film)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseIn Context triple: [Martha Strabel Van Cleve, spouseIn, Heaven Can Wait (1943 film)]
-
A.
spouseInFamily
Indicates that a person is a spouse (married partner) within the context of a specific family unit.
-
B.
spouse
Indicates that two entities are married to each other in a legally or socially recognized partnership.
-
C.
spouseMember
Indicates that one entity is the spouse (married partner) of another entity.
-
D.
spouseOfType
Indicates that one entity is the spouse of another, specifying the type or role of that spousal relationship.
-
E.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
- 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_69f348d61f2081908cad94bc9ffbb671 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fd509e6bc08190b263923c2f40fea3 |
completed | May 8, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69fd4fd1a58881909d4b84de1b24e380 |
completed | May 8, 2026, 2:52 a.m. |
| PDg | Predicate description generation | batch_69fd509cdc5c8190a5f2c451bc0d0b25 |
completed | May 8, 2026, 2:55 a.m. |
Created at: April 30, 2026, 10:36 p.m.