Triple
T20361013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sophia Grey |
E496779
|
entity |
| Predicate | spouseMotivation |
P139834
|
FINISHED |
| Object | financial gain |
—
|
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: financial gain | Statement: [Sophia Grey, spouseMotivation, financial gain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseMotivation Context triple: [Sophia Grey, spouseMotivation, financial gain]
-
A.
spouse
Indicates that two entities are married to each other in a legally or socially recognized partnership.
-
B.
spouseAction
Indicates that one person performs an action toward or on their spouse within the context of a marital relationship.
-
C.
spouseInFamily
Indicates that a person is a spouse (married partner) within the context of a specific family unit.
-
D.
spouseCharacteristic
Indicates that a particular characteristic, trait, or attribute is associated with a person’s spouse within the relationship.
-
E.
spouseFamily
Indicates a family relationship formed through marriage, such as between a person and their spouse’s relatives.
- 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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6786de5988190827584358c9db147 |
completed | April 20, 2026, 7:03 p.m. |
| PD | Predicate disambiguation | batch_69e57648be3c81908256838228cabf5c |
completed | April 20, 2026, 12:41 a.m. |
| PDg | Predicate description generation | batch_69e58d7481508190a87c8b88f9df9879 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:25 a.m.