Triple
T31890081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Check Yes or No |
E814122
|
entity |
| Predicate | hasLaterSetting |
P197062
|
FINISHED |
| Object | adulthood marriage |
—
|
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: adulthood marriage | Statement: [Check Yes or No, hasLaterSetting, adulthood marriage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLaterSetting Context triple: [Check Yes or No, hasLaterSetting, adulthood marriage]
-
A.
hasLaterMember
Indicates that one member in an ordered sequence occurs later than another member in that same sequence.
-
B.
hasLaterTitle
Indicates that one title occurs chronologically after another title in a sequence or timeline.
-
C.
hasSetting
Indicates that an entity takes place, occurs, or exists within a particular environment, context, or location.
-
D.
hasLaterProponent
Indicates that an idea, theory, or position was subsequently supported or advocated by a later individual or group.
-
E.
hasLaterCapital
Indicates that one entity’s designation or establishment as a capital city occurred later in time than that of another entity.
- 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_69f348ef817481908440e2250319bcc8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe766490c081908c49c8cc07d0ae9b |
completed | May 8, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69fe75bb5f4481908572a5ffcbdc5154 |
completed | May 8, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69fe7663b5bc81909524c40d3a172512 |
completed | May 8, 2026, 11:48 p.m. |
Created at: April 30, 2026, 11:57 p.m.