Triple
T33518305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nancy Sykes |
E858430
|
entity |
| Predicate | marriageStatusWithEdAsner |
P193265
|
FINISHED |
| Object | divorced |
—
|
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: divorced | Statement: [Nancy Sykes, marriageStatusWithEdAsner, divorced]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageStatusWithEdAsner Context triple: [Nancy Sykes, marriageStatusWithEdAsner, divorced]
-
A.
marriageStatusWithEdwardGKayeMartin
Indicates the marital relationship status that an entity has with Edward G. Kaye-Martin.
-
B.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
C.
marriageStatusWithLonChaney
Indicates the marital relationship status that an entity has (or had) with Lon Chaney.
-
D.
parentsMarriageStatus
Indicates the marital status relationship between an individual’s parents (e.g., married, divorced, separated, never married).
-
E.
formerHusbandOf
Indicates that one person was previously the husband of another person, but the marital relationship has since ended.
- 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_69f349781c6c819082c516b260efe7e2 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd3d46d1f48190a1b20dd063224b7d |
completed | May 8, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69fd3ae1510c81908fe1280efc17feee |
completed | May 8, 2026, 1:22 a.m. |
| PDg | Predicate description generation | batch_69fd3d45ccb8819082f15e60bd33afc9 |
completed | May 8, 2026, 1:32 a.m. |
Created at: May 1, 2026, 1:39 a.m.