Triple
T26284404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madam Prime Minister |
E661089
|
entity |
| Predicate | usedInSituation |
P25490
|
FINISHED |
| Object | parliamentary debates |
—
|
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: parliamentary debates | Statement: [Madam Prime Minister, usedInSituation, parliamentary debates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInSituation Context triple: [Madam Prime Minister, usedInSituation, parliamentary debates]
-
A.
usedInCase
Indicates that something (such as an item, method, or piece of information) is employed or applied within a particular case or instance.
-
B.
usedAgainst
Indicates that one entity is employed, applied, or deployed in opposition to, or for the purpose of affecting, another entity.
-
C.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
D.
usedInWork
Indicates that something (such as a concept, method, material, or component) is employed or applied within a particular work, project, or creation.
-
E.
areUsedIn
chosen
Indicates that certain entities serve as components, tools, or resources within a particular process, context, or application.
- 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_69ee812bbd448190be4d7478b057990a |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f6a28c7c148190bfc980aad9f678ca |
completed | May 3, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69f69fe1e3c88190830bb2e9f407357e |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 26, 2026, 10:03 p.m.