Triple
T34960239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Earl of Hopetoun |
E1008232
|
entity |
| Predicate | holdersPlayedRoleIn |
P182137
|
FINISHED |
| Object | British public life |
—
|
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: British public life | Statement: [Earl of Hopetoun, holdersPlayedRoleIn, British public life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: holdersPlayedRoleIn Context triple: [Earl of Hopetoun, holdersPlayedRoleIn, British public life]
-
A.
hasPlayedRole
Indicates that an entity has performed or portrayed a particular role or character in some context (such as a film, play, or production).
-
B.
playsInRole
Indicates that an entity performs or appears in a specific role within a production, event, or context.
-
C.
playedKeyRoleIn
Indicates that an entity had a major, influential, or decisive impact on the occurrence, outcome, or success of another entity or event.
-
D.
hasHumanCharacterRole
Indicates that an entity is assigned a role or function specifically associated with a human character within a context such as a story, performance, or representation.
-
E.
hasPlayingRole
Indicates that an entity participates in an activity, event, or performance in a specific playing role or capacity.
- 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_69f76dc69564819099e9e78aed6ff0a6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78710282c81909146dc0be91e983f |
completed | May 3, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f784162134819098413482ef52042f |
completed | May 3, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69f7870dfe108190996c0c68630edc7f |
completed | May 3, 2026, 5:34 p.m. |
Created at: May 3, 2026, 4 p.m.