Triple
T7773751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caroline Campbell |
E179136
|
entity |
| Predicate | titleThrough |
P78249
|
FINISHED |
| Object | marriage into the Scott family |
—
|
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: marriage into the Scott family | Statement: [Caroline Campbell, titleThrough, marriage into the Scott family]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleThrough Context triple: [Caroline Campbell, titleThrough, marriage into the Scott family]
-
A.
title
Indicates that one entity serves as the formal name or designation of another entity.
-
B.
titles
Indicates that one entity holds a formal title, designation, or name associated with another entity.
-
C.
titleRepresents
Indicates that a given title stands for, denotes, or symbolizes a particular concept, role, work, or entity.
-
D.
titleVariant
Indicates that one title is an alternative or variant form of another title referring to the same work or entity.
-
E.
titleStart
Indicates that one entity’s title begins with the text or substring represented by the other 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_69c69f30602c819082ab52cd4af5c592 |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c70461b3e48190bf1e4d4f9e6bb08e |
completed | March 27, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69c7016f4ce881909c2e9f610255187b |
completed | March 27, 2026, 10:15 p.m. |
| PDg | Predicate description generation | batch_69c702a78edc819090c3448d33c8c381 |
completed | March 27, 2026, 10:20 p.m. |
Created at: March 27, 2026, 4:11 p.m.