Triple
T38522251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucille Cameron |
E922513
|
entity |
| Predicate | countryOfMarriageControversy |
P108722
|
FINISHED |
| Object | United States |
E14
|
NE 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: United States | Statement: [Lucille Cameron, countryOfMarriageControversy, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfMarriageControversy Context triple: [Lucille Cameron, countryOfMarriageControversy, United States]
-
A.
marriageControversyInvolved
Indicates that an entity is involved in a dispute, scandal, or public controversy related to a marriage.
-
B.
marriagePartnerOfControversialFigure
Indicates that one entity is the spouse of a figure who is widely regarded as controversial.
-
C.
marriageDefied
Indicates that a marriage went against, resisted, or violated expected norms, rules, or prohibitions.
-
D.
marriageTerritory
chosen
Indicates that a marriage is legally or socially recognized within a specific geographic or jurisdictional territory.
-
E.
typeOfMarriagePolitics
Indicates the political or legal framework governing a particular type of marriage, such as its recognition, regulation, or associated policies.
- F. None of above.
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_69f76ea5f5588190bd0b28c82e975640 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41d640380c819086a4dd80cfe6b1c8 |
completed | June 29, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:32 p.m.