Triple
T3851113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Sarum (UK Parliament constituency) |
E85295
|
entity |
| Predicate | parliamentarySeats |
P51937
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Old Sarum (UK Parliament constituency), parliamentarySeats, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parliamentarySeats Context triple: [Old Sarum (UK Parliament constituency), parliamentarySeats, 2]
-
A.
legislativeAssemblySeats
Indicates the number of seats an entity holds or is allocated in a legislative assembly.
-
B.
legislativeCouncilSeats
Indicates the number of seats held or allocated in a legislative council within a given political or administrative context.
-
C.
seatsWonIn2019ParliamentaryElection
Indicates the number of seats an entity secured in the 2019 parliamentary election.
-
D.
proportionalRepresentationSeats
Indicates that the number of seats allocated to an entity is determined according to a proportional representation system based on its share of votes or support.
-
E.
numberOfSeatsWonIn2019ParliamentaryElection
Indicates the number of seats an entity won in the 2019 parliamentary election.
- 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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeebd0feb081909cc1d5bf41e4acd6 |
completed | March 9, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69aee750377c8190af70c79768c0edd8 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aee8d9b328819080158be59e5bcc97 |
completed | March 9, 2026, 3:35 p.m. |
Created at: March 9, 2026, 3:19 p.m.