Triple
T3822766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sikorski statue in London |
E88613
|
entity |
| Predicate | honoursRole |
P51002
|
FINISHED |
| Object | Prime Minister of the Polish government-in-exile |
—
|
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: Prime Minister of the Polish government-in-exile | Statement: [Sikorski statue in London, honoursRole, Prime Minister of the Polish government-in-exile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: honoursRole Context triple: [Sikorski statue in London, honoursRole, Prime Minister of the Polish government-in-exile]
-
A.
honoursSystemRole
Indicates that one entity respects, preserves, or correctly applies the designated system-level role of another entity or process.
-
B.
honoursPosition
Indicates that one entity holds or is recognized with an honorary or distinguished position in relation to another entity.
-
C.
honorsRole
chosen
Indicates that one entity formally recognizes and respects the position, title, or role held by another entity.
-
D.
honoursTitle
Indicates that an entity holds or is designated by a formal honorific or honorary title.
-
E.
honourType
Indicates the specific category or classification of an honour or award associated with an entity.
- 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_69aed9538cf881909d9ce8ca4ac7c18c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee74a2bc081909b237df8b1e27653 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:17 p.m.