Triple
T35913703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hester Stanhope, Viscountess Mahon |
E1038688
|
entity |
| Predicate | hasTitleThrough |
P69419
|
FINISHED |
| Object | 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: marriage | Statement: [Hester Stanhope, Viscountess Mahon, hasTitleThrough, marriage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleThrough Context triple: [Hester Stanhope, Viscountess Mahon, hasTitleThrough, marriage]
-
A.
hasTitleIn
Indicates that an entity holds or is associated with a specific title within a particular context, domain, or language.
-
B.
hasTitleFrom
chosen
Indicates that one entity holds or uses a title that originates from, or is conferred by, another entity.
-
C.
hasTitleOf
Indicates that one entity holds, bears, or is designated by the official title, name, or rank specified by another entity.
-
D.
hasTitleOver
Indicates that one entity holds a formal title, rank, or designation in relation to another entity.
-
E.
hasTitleName
Indicates that an entity possesses or is associated with a specific title or name.
- F. None of above.
Provenance (3 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_69f76e2259608190bf6788a132e0d139 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fdec5ffe088190ac5505f26c6cff18 |
completed | May 8, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69fdeae15f1c81908fc63fbc1b028d2e |
completed | May 8, 2026, 1:53 p.m. |
Created at: May 3, 2026, 4:07 p.m.