Triple
T30117914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Effie Wise Ochs |
E765474
|
entity |
| Predicate | marriedToPublisherOf |
P157264
|
FINISHED |
| Object | The New York Times |
—
|
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: The New York Times | Statement: [Effie Wise Ochs, marriedToPublisherOf, The New York Times]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriedToPublisherOf Context triple: [Effie Wise Ochs, marriedToPublisherOf, The New York Times]
-
A.
spouseOfPublisherOf
chosen
Indicates that one entity is the spouse of the person or organization that publishes another entity.
-
B.
hasAuthorMarriedName
Indicates that an author’s married surname or full married name is associated with them, typically differing from their birth or maiden name.
-
C.
spouseOfCreatorOf
Indicates that one entity is the spouse of the person who created another entity.
-
D.
hasAuthorSpouse
Indicates that the spouse of the subject entity is the author of the related work or entity.
-
E.
marriedToBeforeFameOf
Indicates that one person was married to another person before the latter became famous.
- 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_69f2247716748190ae4f16998f49ddf1 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7675b12848190a3569cfda29c5b0e |
completed | May 3, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69f762f4b59481909f70074f11825bfb |
completed | May 3, 2026, 3 p.m. |
Created at: April 29, 2026, 7:12 p.m.