Triple
T17267331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | December 2005 Iraqi parliamentary election |
E419162
|
entity |
| Predicate | turnoutApproximate |
P29796
|
FINISHED |
| Object | around 70% |
—
|
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: around 70% | Statement: [December 2005 Iraqi parliamentary election, turnoutApproximate, around 70%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turnoutApproximate Context triple: [December 2005 Iraqi parliamentary election, turnoutApproximate, around 70%]
-
A.
turnout
chosen
Indicates the number or proportion of participants who attend or take part in an event or activity.
-
B.
hasApproximateNumberOfPeople
Indicates that an entity is associated with an estimated or approximate count of people, rather than an exact number.
-
C.
approximateAudienceSize
Indicates an estimated number of individuals or entities that are expected to be reached or affected in a given context.
-
D.
approximateNumberOfVotersBefore
Indicates that one value represents an estimated count of voters that existed prior to a specified point in time or event.
-
E.
passengersCountApproximate
Indicates that the number of passengers involved is given as an approximate or estimated count rather than an exact figure.
- 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_69d886da626481908a14ce7830329a35 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42f45bf608190bcb48783d0d6fb85 |
completed | April 19, 2026, 1:26 a.m. |
| PD | Predicate disambiguation | batch_69e3832a284481908a8a3da7ac91de5a |
completed | April 18, 2026, 1:12 p.m. |
Created at: April 10, 2026, 5:40 a.m.