Triple
T25737815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Leddy |
E648123
|
entity |
| Predicate | spouseOfNotableBook |
P161452
|
FINISHED |
| Object | I Heard You Paint Houses |
—
|
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: I Heard You Paint Houses | Statement: [Mary Leddy, spouseOfNotableBook, I Heard You Paint Houses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseOfNotableBook Context triple: [Mary Leddy, spouseOfNotableBook, I Heard You Paint Houses]
-
A.
hasAuthorSpouse
Indicates that the spouse of the subject entity is the author of the related work or entity.
-
B.
spouse notableWork
chosen
Indicates that a person's spouse is significantly associated with a particular notable work.
-
C.
spouseNotableFor
Indicates that a person's spouse is recognized or distinguished for a particular achievement, role, or characteristic.
-
D.
spouseOfPublisherOf
Indicates that one entity is the spouse of the person or organization that publishes another entity.
-
E.
authorSpouseOrigin
Indicates that the spouse of the author comes from or is originally associated with a specified place or origin.
- 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_69e7ab306eec8190b05c312c6ab186b8 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6640168948190811bd5f933a87cf5 |
completed | May 2, 2026, 8:52 p.m. |
| PD | Predicate disambiguation | batch_69f6633451948190bcc0410602bb4914 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 22, 2026, 3:36 a.m.