Triple
T11876502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gretna Green |
E282540
|
entity |
| Predicate | marriageAgeRequirementHistorically |
P102008
|
FINISHED |
| Object | 16 without parental consent |
—
|
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: 16 without parental consent | Statement: [Gretna Green, marriageAgeRequirementHistorically, 16 without parental consent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageAgeRequirementHistorically Context triple: [Gretna Green, marriageAgeRequirementHistorically, 16 without parental consent]
-
A.
ageAtMarriage
Indicates the age a person was when they got married.
-
B.
betrothalAge
Indicates the age at which a person becomes formally engaged to be married.
-
C.
marriageBefore
Indicates that one marriage event occurred earlier in time than another marriage event.
-
D.
numberOfMarriages
Indicates the total count of times an entity has been legally married.
-
E.
marriageDuration
Indicates the length of time that a marriage relationship has existed between two spouses.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d39d2934819093b9f7006f45e5cb |
completed | April 10, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69d8bb272f88819090c37c944c5a60ab |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8d399d58c81908dab572aa82426d7 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 8, 2026, 9:44 p.m.